diff options
| -rw-r--r-- | bslmm.cpp | 1928 | ||||
| -rw-r--r-- | bslmm.h | 146 | ||||
| -rwxr-xr-x | gemma | bin | 4823751 -> 0 bytes | |||
| -rw-r--r-- | gemma.cpp | 1864 | ||||
| -rw-r--r-- | gemma.h | 52 | ||||
| -rw-r--r-- | gzstream.cpp | 165 | ||||
| -rw-r--r-- | gzstream.h | 121 | ||||
| -rw-r--r-- | io.cpp | 1396 | ||||
| -rw-r--r-- | io.h | 79 | ||||
| -rw-r--r-- | lapack.cpp | 609 | ||||
| -rw-r--r-- | lapack.h | 53 | ||||
| -rw-r--r-- | lm.cpp | 572 | ||||
| -rw-r--r-- | lm.h | 75 | ||||
| -rw-r--r-- | lmm.cpp | 1771 | ||||
| -rw-r--r-- | lmm.h | 111 | ||||
| -rw-r--r-- | main.cpp | 86 | ||||
| -rw-r--r-- | mathfunc.cpp | 310 | ||||
| -rw-r--r-- | mathfunc.h | 41 | ||||
| -rw-r--r-- | mvlmm.cpp | 3749 | ||||
| -rw-r--r-- | mvlmm.h | 94 | ||||
| -rw-r--r-- | param.cpp | 849 | ||||
| -rw-r--r-- | param.h | 232 | ||||
| -rw-r--r-- | prdt.cpp | 544 | ||||
| -rw-r--r-- | prdt.h | 81 | ||||
| -rw-r--r-- | vc.cpp | 443 | ||||
| -rw-r--r-- | vc.h | 82 |
26 files changed, 0 insertions, 15453 deletions
diff --git a/bslmm.cpp b/bslmm.cpp deleted file mode 100644 index 55a05ca..0000000 --- a/bslmm.cpp +++ /dev/null @@ -1,1928 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - -#include <iostream> -#include <fstream> -#include <sstream> - -#include <iomanip> -#include <cmath> -#include <iostream> -#include <stdio.h> -#include <stdlib.h> -#include <ctime> -#include <cstring> -#include <algorithm> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" -#include "gsl/gsl_eigen.h" -#include "gsl/gsl_randist.h" -#include "gsl/gsl_cdf.h" -#include "gsl/gsl_roots.h" - - - - -#include "lapack.h" - -#ifdef FORCE_FLOAT -#include "param_float.h" -#include "bslmm_float.h" -#include "lmm_float.h" //for class FUNC_PARAM and MatrixCalcLR -#include "lm_float.h" -#include "mathfunc_float.h" //for function CenterVector -#else -#include "param.h" -#include "bslmm.h" -#include "lmm.h" -#include "lm.h" -#include "mathfunc.h" -#endif - -using namespace std; - - - - -void BSLMM::CopyFromParam (PARAM &cPar) -{ - a_mode=cPar.a_mode; - d_pace=cPar.d_pace; - - file_bfile=cPar.file_bfile; - file_geno=cPar.file_geno; - file_out=cPar.file_out; - path_out=cPar.path_out; - - l_min=cPar.h_min; - l_max=cPar.h_max; - n_region=cPar.n_region; - pve_null=cPar.pve_null; - pheno_mean=cPar.pheno_mean; - - time_UtZ=0.0; - time_Omega=0.0; - n_accept=0; - - h_min=cPar.h_min; - h_max=cPar.h_max; - h_scale=cPar.h_scale; - rho_min=cPar.rho_min; - rho_max=cPar.rho_max; - rho_scale=cPar.rho_scale; - logp_min=cPar.logp_min; - logp_max=cPar.logp_max; - logp_scale=cPar.logp_scale; - - s_min=cPar.s_min; - s_max=cPar.s_max; - w_step=cPar.w_step; - s_step=cPar.s_step; - r_pace=cPar.r_pace; - w_pace=cPar.w_pace; - n_mh=cPar.n_mh; - geo_mean=cPar.geo_mean; - randseed=cPar.randseed; - trace_G=cPar.trace_G; - - ni_total=cPar.ni_total; - ns_total=cPar.ns_total; - ni_test=cPar.ni_test; - ns_test=cPar.ns_test; - n_cvt=cPar.n_cvt; - - indicator_idv=cPar.indicator_idv; - indicator_snp=cPar.indicator_snp; - snpInfo=cPar.snpInfo; - - return; -} - - -void BSLMM::CopyToParam (PARAM &cPar) -{ - cPar.time_UtZ=time_UtZ; - cPar.time_Omega=time_Omega; - cPar.time_Proposal=time_Proposal; - cPar.cHyp_initial=cHyp_initial; - cPar.n_accept=n_accept; - cPar.pheno_mean=pheno_mean; - cPar.randseed=randseed; - - return; -} - - - -void BSLMM::WriteBV (const gsl_vector *bv) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".bv.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - size_t t=0; - for (size_t i=0; i<ni_total; ++i) { - if (indicator_idv[i]==0) { - outfile<<"NA"<<endl; - } - else { - outfile<<scientific<<setprecision(6)<<gsl_vector_get(bv, t)<<endl; - t++; - } - } - - outfile.clear(); - outfile.close(); - return; -} - - - - -void BSLMM::WriteParam (vector<pair<double, double> > &beta_g, const gsl_vector *alpha, const size_t w) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".param.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - outfile<<"chr"<<"\t"<<"rs"<<"\t" - <<"ps"<<"\t"<<"n_miss"<<"\t"<<"alpha"<<"\t" - <<"beta"<<"\t"<<"gamma"<<endl; - - size_t t=0; - for (size_t i=0; i<ns_total; ++i) { - if (indicator_snp[i]==0) {continue;} - - outfile<<snpInfo[i].chr<<"\t"<<snpInfo[i].rs_number<<"\t" - <<snpInfo[i].base_position<<"\t"<<snpInfo[i].n_miss<<"\t"; - - outfile<<scientific<<setprecision(6)<<gsl_vector_get(alpha, t)<<"\t"; - if (beta_g[t].second!=0) { - outfile<<beta_g[t].first/beta_g[t].second<<"\t"<<beta_g[t].second/(double)w<<endl; - } - else { - outfile<<0.0<<"\t"<<0.0<<endl; - } - t++; - } - - outfile.clear(); - outfile.close(); - return; -} - - -void BSLMM::WriteParam (const gsl_vector *alpha) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".param.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - outfile<<"chr"<<"\t"<<"rs"<<"\t" - <<"ps"<<"\t"<<"n_miss"<<"\t"<<"alpha"<<"\t" - <<"beta"<<"\t"<<"gamma"<<endl; - - size_t t=0; - for (size_t i=0; i<ns_total; ++i) { - if (indicator_snp[i]==0) {continue;} - - outfile<<snpInfo[i].chr<<"\t"<<snpInfo[i].rs_number<<"\t" - <<snpInfo[i].base_position<<"\t"<<snpInfo[i].n_miss<<"\t"; - outfile<<scientific<<setprecision(6)<<gsl_vector_get(alpha, t)<<"\t"; - outfile<<0.0<<"\t"<<0.0<<endl; - t++; - } - - outfile.clear(); - outfile.close(); - return; -} - - -void BSLMM::WriteResult (const int flag, const gsl_matrix *Result_hyp, const gsl_matrix *Result_gamma, const size_t w_col) -{ - string file_gamma, file_hyp; - file_gamma=path_out+"/"+file_out; - file_gamma+=".gamma.txt"; - file_hyp=path_out+"/"+file_out; - file_hyp+=".hyp.txt"; - - ofstream outfile_gamma, outfile_hyp; - - if (flag==0) { - outfile_gamma.open (file_gamma.c_str(), ofstream::out); - outfile_hyp.open (file_hyp.c_str(), ofstream::out); - if (!outfile_gamma) {cout<<"error writing file: "<<file_gamma<<endl; return;} - if (!outfile_hyp) {cout<<"error writing file: "<<file_hyp<<endl; return;} - - outfile_hyp<<"h \t pve \t rho \t pge \t pi \t n_gamma"<<endl; - - for (size_t i=0; i<s_max; ++i) { - outfile_gamma<<"s"<<i<<"\t"; - } - outfile_gamma<<endl; - } - else { - outfile_gamma.open (file_gamma.c_str(), ofstream::app); - outfile_hyp.open (file_hyp.c_str(), ofstream::app); - if (!outfile_gamma) {cout<<"error writing file: "<<file_gamma<<endl; return;} - if (!outfile_hyp) {cout<<"error writing file: "<<file_hyp<<endl; return;} - - size_t w; - if (w_col==0) {w=w_pace;} - else {w=w_col;} - - for (size_t i=0; i<w; ++i) { - outfile_hyp<<scientific; - for (size_t j=0; j<4; ++j) { - outfile_hyp<<setprecision(6)<<gsl_matrix_get (Result_hyp, i, j)<<"\t"; - } - outfile_hyp<<setprecision(6)<<exp(gsl_matrix_get (Result_hyp, i, 4))<<"\t"; - outfile_hyp<<(int)gsl_matrix_get (Result_hyp, i, 5)<<"\t"; - outfile_hyp<<endl; - } - - for (size_t i=0; i<w; ++i) { - for (size_t j=0; j<s_max; ++j) { - outfile_gamma<<(int)gsl_matrix_get (Result_gamma, i, j)<<"\t"; - } - outfile_gamma<<endl; - } - - } - - outfile_hyp.close(); - outfile_hyp.clear(); - outfile_gamma.close(); - outfile_gamma.clear(); - return; -} - - - -void BSLMM::CalcPgamma (double *p_gamma) -{ - double p, s=0.0; - for (size_t i=0; i<ns_test; ++i) { - p=0.7*gsl_ran_geometric_pdf (i+1, 1.0/geo_mean)+0.3/(double)ns_test; - p_gamma[i]=p; - s+=p; - } - for (size_t i=0; i<ns_test; ++i) { - p=p_gamma[i]; - p_gamma[i]=p/s; - } - return; -} - - - -void BSLMM::SetXgamma (gsl_matrix *Xgamma, const gsl_matrix *X, vector<size_t> &rank) -{ - size_t pos; - for (size_t i=0; i<rank.size(); ++i) { - pos=mapRank2pos[rank[i]]; - gsl_vector_view Xgamma_col=gsl_matrix_column (Xgamma, i); - gsl_vector_const_view X_col=gsl_matrix_const_column (X, pos); - gsl_vector_memcpy (&Xgamma_col.vector, &X_col.vector); - } - - return; -} - - - -double BSLMM::CalcPveLM (const gsl_matrix *UtXgamma, const gsl_vector *Uty, const double sigma_a2) -{ - double pve, var_y; - - gsl_matrix *Omega=gsl_matrix_alloc (UtXgamma->size2, UtXgamma->size2); - gsl_vector *Xty=gsl_vector_alloc (UtXgamma->size2); - gsl_vector *OiXty=gsl_vector_alloc (UtXgamma->size2); - - gsl_matrix_set_identity (Omega); - gsl_matrix_scale (Omega, 1.0/sigma_a2); - -#ifdef WITH_LAPACK - lapack_dgemm ((char *)"T", (char *)"N", 1.0, UtXgamma, UtXgamma, 1.0, Omega); -#else - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, UtXgamma, UtXgamma, 1.0, Omega); -#endif - gsl_blas_dgemv (CblasTrans, 1.0, UtXgamma, Uty, 0.0, Xty); - - CholeskySolve(Omega, Xty, OiXty); - - gsl_blas_ddot (Xty, OiXty, &pve); - gsl_blas_ddot (Uty, Uty, &var_y); - - pve/=var_y; - - gsl_matrix_free (Omega); - gsl_vector_free (Xty); - gsl_vector_free (OiXty); - - return pve; -} - - -void BSLMM::InitialMCMC (const gsl_matrix *UtX, const gsl_vector *Uty, vector<size_t> &rank, class HYPBSLMM &cHyp, vector<pair<size_t, double> > &pos_loglr) -{ - double q_genome=gsl_cdf_chisq_Qinv(0.05/(double)ns_test, 1); - - cHyp.n_gamma=0; - for (size_t i=0; i<pos_loglr.size(); ++i) { - if (2.0*pos_loglr[i].second>q_genome) {cHyp.n_gamma++;} - } - if (cHyp.n_gamma<10) {cHyp.n_gamma=10;} - - if (cHyp.n_gamma>s_max) {cHyp.n_gamma=s_max;} - if (cHyp.n_gamma<s_min) {cHyp.n_gamma=s_min;} - - rank.clear(); - for (size_t i=0; i<cHyp.n_gamma; ++i) { - rank.push_back(i); - } - - cHyp.logp=log((double)cHyp.n_gamma/(double)ns_test); - cHyp.h=pve_null; - - if (cHyp.logp==0) {cHyp.logp=-0.000001;} - if (cHyp.h==0) {cHyp.h=0.1;} - - gsl_matrix *UtXgamma=gsl_matrix_alloc (ni_test, cHyp.n_gamma); - SetXgamma (UtXgamma, UtX, rank); - double sigma_a2; - if (trace_G!=0) { - sigma_a2=cHyp.h*1.0/(trace_G*(1-cHyp.h)*exp(cHyp.logp)*(double)ns_test); - } else { - sigma_a2=cHyp.h*1.0/( (1-cHyp.h)*exp(cHyp.logp)*(double)ns_test); - } - if (sigma_a2==0) {sigma_a2=0.025;} - cHyp.rho=CalcPveLM (UtXgamma, Uty, sigma_a2)/cHyp.h; - gsl_matrix_free (UtXgamma); - - if (cHyp.rho>1.0) {cHyp.rho=1.0;} - - if (cHyp.h<h_min) {cHyp.h=h_min;} - if (cHyp.h>h_max) {cHyp.h=h_max;} - if (cHyp.rho<rho_min) {cHyp.rho=rho_min;} - if (cHyp.rho>rho_max) {cHyp.rho=rho_max;} - if (cHyp.logp<logp_min) {cHyp.logp=logp_min;} - if (cHyp.logp>logp_max) {cHyp.logp=logp_max;} - - -// if (fix_sigma>=0) { -// fix_sigma=cHyp.h; -// rho_max=1-cHyp.h; -// cHyp.rho=rho_max/2.0; -// } - - //Initial for grid sampling: -// cHyp.h=0.225; -// cHyp.rho=1.0; -// cHyp.logp=-4.835429; - - cout<<"initial value of h = "<<cHyp.h<<endl; - cout<<"initial value of rho = "<<cHyp.rho<<endl; - cout<<"initial value of pi = "<<exp(cHyp.logp)<<endl; - cout<<"initial value of |gamma| = "<<cHyp.n_gamma<<endl; - - return; -} - - - -double BSLMM::CalcPosterior (const gsl_vector *Uty, const gsl_vector *K_eval, gsl_vector *Utu, gsl_vector *alpha_prime, class HYPBSLMM &cHyp) -{ - double sigma_b2=cHyp.h*(1.0-cHyp.rho)/(trace_G*(1-cHyp.h)); - - gsl_vector *Utu_rand=gsl_vector_alloc (Uty->size); - gsl_vector *weight_Hi=gsl_vector_alloc (Uty->size); - - double logpost=0.0; - double d, ds, uy, Hi_yy=0, logdet_H=0.0; - for (size_t i=0; i<ni_test; ++i) { - d=gsl_vector_get (K_eval, i)*sigma_b2; - ds=d/(d+1.0); - d=1.0/(d+1.0); - gsl_vector_set (weight_Hi, i, d); - - logdet_H-=log(d); - uy=gsl_vector_get (Uty, i); - Hi_yy+=d*uy*uy; - - gsl_vector_set (Utu_rand, i, gsl_ran_gaussian(gsl_r, 1)*sqrt(ds)); - } - - //sample tau - double tau=1.0; - if (a_mode==11) {tau = gsl_ran_gamma (gsl_r, (double)ni_test/2.0, 2.0/Hi_yy); } - - //sample alpha - gsl_vector_memcpy (alpha_prime, Uty); - gsl_vector_mul (alpha_prime, weight_Hi); - gsl_vector_scale (alpha_prime, sigma_b2); - - //sample u - gsl_vector_memcpy (Utu, alpha_prime); - gsl_vector_mul (Utu, K_eval); - if (a_mode==11) {gsl_vector_scale (Utu_rand, sqrt(1.0/tau));} - gsl_vector_add (Utu, Utu_rand); - - //for quantitative traits, calculate pve and ppe - if (a_mode==11) { - gsl_blas_ddot (Utu, Utu, &d); - cHyp.pve=d/(double)ni_test; - cHyp.pve/=cHyp.pve+1.0/tau; - cHyp.pge=0.0; - } - - //calculate likelihood - logpost=-0.5*logdet_H; - if (a_mode==11) {logpost-=0.5*(double)ni_test*log(Hi_yy);} - else {logpost-=0.5*Hi_yy;} - - logpost+=((double)cHyp.n_gamma-1.0)*cHyp.logp+((double)ns_test-(double)cHyp.n_gamma)*log(1-exp(cHyp.logp)); - - gsl_vector_free (Utu_rand); - gsl_vector_free (weight_Hi); - - return logpost; -} - - -double BSLMM::CalcPosterior (const gsl_matrix *UtXgamma, const gsl_vector *Uty, const gsl_vector *K_eval, gsl_vector *UtXb, gsl_vector *Utu, gsl_vector *alpha_prime, gsl_vector *beta, class HYPBSLMM &cHyp) -{ - clock_t time_start; - - double sigma_a2=cHyp.h*cHyp.rho/(trace_G*(1-cHyp.h)*exp(cHyp.logp)*(double)ns_test); - double sigma_b2=cHyp.h*(1.0-cHyp.rho)/(trace_G*(1-cHyp.h)); - - double logpost=0.0; - double d, ds, uy, P_yy=0, logdet_O=0.0, logdet_H=0.0; - - gsl_matrix *UtXgamma_eval=gsl_matrix_alloc (UtXgamma->size1, UtXgamma->size2); - gsl_matrix *Omega=gsl_matrix_alloc (UtXgamma->size2, UtXgamma->size2); - gsl_vector *XtHiy=gsl_vector_alloc (UtXgamma->size2); - gsl_vector *beta_hat=gsl_vector_alloc (UtXgamma->size2); - gsl_vector *Utu_rand=gsl_vector_alloc (UtXgamma->size1); - gsl_vector *weight_Hi=gsl_vector_alloc (UtXgamma->size1); - - gsl_matrix_memcpy (UtXgamma_eval, UtXgamma); - - logdet_H=0.0; P_yy=0.0; - for (size_t i=0; i<ni_test; ++i) { - gsl_vector_view UtXgamma_row=gsl_matrix_row (UtXgamma_eval, i); - d=gsl_vector_get (K_eval, i)*sigma_b2; - ds=d/(d+1.0); - d=1.0/(d+1.0); - gsl_vector_set (weight_Hi, i, d); - - logdet_H-=log(d); - uy=gsl_vector_get (Uty, i); - P_yy+=d*uy*uy; - gsl_vector_scale (&UtXgamma_row.vector, d); - - gsl_vector_set (Utu_rand, i, gsl_ran_gaussian(gsl_r, 1)*sqrt(ds)); - } - - //calculate Omega - gsl_matrix_set_identity (Omega); - - time_start=clock(); -#ifdef WITH_LAPACK - lapack_dgemm ((char *)"T", (char *)"N", sigma_a2, UtXgamma_eval, UtXgamma, 1.0, Omega); -#else - gsl_blas_dgemm (CblasTrans, CblasNoTrans, sigma_a2, UtXgamma_eval, UtXgamma, 1.0, Omega); -#endif - time_Omega+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - - //calculate beta_hat - gsl_blas_dgemv (CblasTrans, 1.0, UtXgamma_eval, Uty, 0.0, XtHiy); - - logdet_O=CholeskySolve(Omega, XtHiy, beta_hat); - - gsl_vector_scale (beta_hat, sigma_a2); - - gsl_blas_ddot (XtHiy, beta_hat, &d); - P_yy-=d; - - //sample tau - double tau=1.0; - if (a_mode==11) {tau =gsl_ran_gamma (gsl_r, (double)ni_test/2.0, 2.0/P_yy); } - - //sample beta - for (size_t i=0; i<beta->size; i++) - { - d=gsl_ran_gaussian(gsl_r, 1); - gsl_vector_set(beta, i, d); - } - gsl_blas_dtrsv(CblasUpper, CblasNoTrans, CblasNonUnit, Omega, beta); - - - //it compuates inv(L^T(Omega)) %*% beta; - gsl_vector_scale(beta, sqrt(sigma_a2/tau)); - gsl_vector_add(beta, beta_hat); - gsl_blas_dgemv (CblasNoTrans, 1.0, UtXgamma, beta, 0.0, UtXb); - - //sample alpha - gsl_vector_memcpy (alpha_prime, Uty); - gsl_vector_sub (alpha_prime, UtXb); - gsl_vector_mul (alpha_prime, weight_Hi); - gsl_vector_scale (alpha_prime, sigma_b2); - - //sample u - gsl_vector_memcpy (Utu, alpha_prime); - gsl_vector_mul (Utu, K_eval); - - if (a_mode==11) {gsl_vector_scale (Utu_rand, sqrt(1.0/tau));} - gsl_vector_add (Utu, Utu_rand); - - - //for quantitative traits, calculate pve and pge - if (a_mode==11) { - gsl_blas_ddot (UtXb, UtXb, &d); - cHyp.pge=d/(double)ni_test; - - gsl_blas_ddot (Utu, Utu, &d); - cHyp.pve=cHyp.pge+d/(double)ni_test; - - if (cHyp.pve==0) {cHyp.pge=0.0;} - else {cHyp.pge/=cHyp.pve;} - cHyp.pve/=cHyp.pve+1.0/tau; - } - - - gsl_matrix_free (UtXgamma_eval); - gsl_matrix_free (Omega); - gsl_vector_free (XtHiy); - gsl_vector_free (beta_hat); - gsl_vector_free (Utu_rand); - gsl_vector_free (weight_Hi); - - logpost=-0.5*logdet_H-0.5*logdet_O; - if (a_mode==11) {logpost-=0.5*(double)ni_test*log(P_yy);} - else {logpost-=0.5*P_yy;} -// else {logpost+=-0.5*P_yy*tau+0.5*(double)ni_test*log(tau);} - logpost+=((double)cHyp.n_gamma-1.0)*cHyp.logp+((double)ns_test-(double)cHyp.n_gamma)*log(1.0-exp(cHyp.logp)); - - return logpost; -} - - - -//calculate pve and pge, and calculate z_hat for case-control data -void BSLMM::CalcCC_PVEnZ (const gsl_matrix *U, const gsl_vector *Utu, gsl_vector *z_hat, class HYPBSLMM &cHyp) -{ - double d; - - gsl_blas_ddot (Utu, Utu, &d); - cHyp.pve=d/(double)ni_test; - - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Utu, 0.0, z_hat); - - cHyp.pve/=cHyp.pve+1.0; - cHyp.pge=0.0; - - return; -} - - -//calculate pve and pge, and calculate z_hat for case-control data -void BSLMM::CalcCC_PVEnZ (const gsl_matrix *U, const gsl_vector *UtXb, const gsl_vector *Utu, gsl_vector *z_hat, class HYPBSLMM &cHyp) -{ - double d; - gsl_vector *UtXbU=gsl_vector_alloc (Utu->size); - - gsl_blas_ddot (UtXb, UtXb, &d); - cHyp.pge=d/(double)ni_test; - - gsl_blas_ddot (Utu, Utu, &d); - cHyp.pve=cHyp.pge+d/(double)ni_test; - - gsl_vector_memcpy (UtXbU, Utu); - gsl_vector_add (UtXbU, UtXb); - gsl_blas_dgemv (CblasNoTrans, 1.0, U, UtXbU, 0.0, z_hat); - - if (cHyp.pve==0) {cHyp.pge=0.0;} - else {cHyp.pge/=cHyp.pve;} - - cHyp.pve/=cHyp.pve+1.0; - - gsl_vector_free(UtXbU); - return; -} - - - - -void BSLMM::SampleZ (const gsl_vector *y, const gsl_vector *z_hat, gsl_vector *z) -{ - double d1, d2, z_rand=0.0; - for (size_t i=0; i<z->size; ++i) { - d1=gsl_vector_get (y, i); - d2=gsl_vector_get (z_hat, i); - //y is centerred for case control studies - if (d1<=0.0) { - //control, right truncated - do { - z_rand=d2+gsl_ran_gaussian(gsl_r, 1.0); - } while (z_rand>0.0); - } - else { - do { - z_rand=d2+gsl_ran_gaussian(gsl_r, 1.0); - } while (z_rand<0.0); - } - - gsl_vector_set (z, i, z_rand); - } - - return; -} - - - - - -double BSLMM::ProposeHnRho (const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat) -{ - - double h=cHyp_old.h, rho=cHyp_old.rho; - - double d_h=(h_max-h_min)*h_scale, d_rho=(rho_max-rho_min)*rho_scale; - - for (size_t i=0; i<repeat; ++i) { - h=h+(gsl_rng_uniform(gsl_r)-0.5)*d_h; - if (h<h_min) {h=2*h_min-h;} - if (h>h_max) {h=2*h_max-h;} - - rho=rho+(gsl_rng_uniform(gsl_r)-0.5)*d_rho; - if (rho<rho_min) {rho=2*rho_min-rho;} - if (rho>rho_max) {rho=2*rho_max-rho;} - } - /* - //Grid Sampling - for (size_t i=0; i<repeat; ++i) { - if (gsl_rng_uniform(gsl_r)<0.66) {continue;} - h=h+(gsl_rng_uniform_int(gsl_r, 2)-0.5)*0.1; - if (h<h_min) {h=h_max;} - if (h>h_max) {h=h_min;} - } - - for (size_t i=0; i<repeat; ++i) { - if (gsl_rng_uniform(gsl_r)<0.66) {continue;} - rho=rho+(gsl_rng_uniform_int(gsl_r, 2)-0.5)*0.1; - if (rho<rho_min) {rho=rho_max;} - if (rho>rho_max) {rho=rho_min;} - } - */ - cHyp_new.h=h; - cHyp_new.rho=rho; - return 0.0; -} - - -double BSLMM::ProposePi (const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat) -{ - double logp_old=cHyp_old.logp, logp_new=cHyp_old.logp; - double log_ratio=0.0; - - double d_logp=min(0.1, (logp_max-logp_min)*logp_scale); - - for (size_t i=0; i<repeat; ++i) { - logp_new=logp_old+(gsl_rng_uniform(gsl_r)-0.5)*d_logp; - if (logp_new<logp_min) {logp_new=2*logp_min-logp_new;} - if (logp_new>logp_max) {logp_new=2*logp_max-logp_new;} - - log_ratio+=logp_new-logp_old; - logp_old=logp_new; - } - /* - //Grid Sampling - for (size_t i=0; i<repeat; ++i) { - if (gsl_rng_uniform(gsl_r)<0.66) {continue;} - logp_new=logp_old+(gsl_rng_uniform_int(gsl_r, 2)-0.5)*0.5*log(10.0); - if (logp_new<logp_min) {logp_new=logp_max;} - if (logp_new>logp_max) {logp_new=logp_min;} - - log_ratio+=logp_new-logp_old; - logp_old=logp_new; - } - */ - cHyp_new.logp=logp_new; - - return log_ratio; -} - -bool comp_vec (size_t a, size_t b) -{ - return (a < b); -} - - -double BSLMM::ProposeGamma (const vector<size_t> &rank_old, vector<size_t> &rank_new, const double *p_gamma, const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat) -{ - map<size_t, int> mapRank2in; - size_t r; - double unif, logp=0.0; - int flag_gamma; - size_t r_add, r_remove, col_id; - - rank_new.clear(); - if (cHyp_old.n_gamma!=rank_old.size()) {cout<<"size wrong"<<endl;} - - if (cHyp_old.n_gamma!=0) { - for (size_t i=0; i<rank_old.size(); ++i) { - r=rank_old[i]; - rank_new.push_back(r); - mapRank2in[r]=1; - } - } - cHyp_new.n_gamma=cHyp_old.n_gamma; - - for (size_t i=0; i<repeat; ++i) { - unif=gsl_rng_uniform(gsl_r); - - if (unif < 0.40 && cHyp_new.n_gamma<s_max) {flag_gamma=1;} - else if (unif>=0.40 && unif < 0.80 && cHyp_new.n_gamma>s_min) {flag_gamma=2;} - else if (unif>=0.80 && cHyp_new.n_gamma>0 && cHyp_new.n_gamma<ns_test) {flag_gamma=3;} - else {flag_gamma=4;} - - if(flag_gamma==1) {//add a snp; - do { - r_add=gsl_ran_discrete (gsl_r, gsl_t); - } while (mapRank2in.count(r_add)!=0); - - double prob_total=1.0; - for (size_t i=0; i<cHyp_new.n_gamma; ++i) { - r=rank_new[i]; - prob_total-=p_gamma[r]; - } - - mapRank2in[r_add]=1; - rank_new.push_back(r_add); - cHyp_new.n_gamma++; - logp+=-log(p_gamma[r_add]/prob_total)-log((double)cHyp_new.n_gamma); - } - else if (flag_gamma==2) {//delete a snp; - col_id=gsl_rng_uniform_int(gsl_r, cHyp_new.n_gamma); - r_remove=rank_new[col_id]; - - double prob_total=1.0; - for (size_t i=0; i<cHyp_new.n_gamma; ++i) { - r=rank_new[i]; - prob_total-=p_gamma[r]; - } - prob_total+=p_gamma[r_remove]; - - mapRank2in.erase(r_remove); - rank_new.erase(rank_new.begin()+col_id); - logp+=log(p_gamma[r_remove]/prob_total)+log((double)cHyp_new.n_gamma); - cHyp_new.n_gamma--; - } - else if (flag_gamma==3) {//switch a snp; - col_id=gsl_rng_uniform_int(gsl_r, cHyp_new.n_gamma); - r_remove=rank_new[col_id]; - //careful with the proposal - do { - r_add=gsl_ran_discrete (gsl_r, gsl_t); - } while (mapRank2in.count(r_add)!=0); - - double prob_total=1.0; - for (size_t i=0; i<cHyp_new.n_gamma; ++i) { - r=rank_new[i]; - prob_total-=p_gamma[r]; - } - - logp+=log(p_gamma[r_remove]/(prob_total+p_gamma[r_remove]-p_gamma[r_add]) ); - logp-=log(p_gamma[r_add]/prob_total); - - mapRank2in.erase(r_remove); - mapRank2in[r_add]=1; - rank_new.erase(rank_new.begin()+col_id); - rank_new.push_back(r_add); - } - else {logp+=0;}//do not change - } - - stable_sort (rank_new.begin(), rank_new.end(), comp_vec); - - mapRank2in.clear(); - return logp; -} - - - - - - -bool comp_lr (pair<size_t, double> a, pair<size_t, double> b) -{ - return (a.second > b.second); -} - - - - - - - -//if a_mode==13 then Uty==y -void BSLMM::MCMC (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, const gsl_vector *y) { - clock_t time_start; - - class HYPBSLMM cHyp_old, cHyp_new; - - gsl_matrix *Result_hyp=gsl_matrix_alloc (w_pace, 6); - gsl_matrix *Result_gamma=gsl_matrix_alloc (w_pace, s_max); - - gsl_vector *alpha_prime=gsl_vector_alloc (ni_test); - gsl_vector *alpha_new=gsl_vector_alloc (ni_test); - gsl_vector *alpha_old=gsl_vector_alloc (ni_test); - gsl_vector *Utu=gsl_vector_alloc (ni_test); - gsl_vector *Utu_new=gsl_vector_alloc (ni_test); - gsl_vector *Utu_old=gsl_vector_alloc (ni_test); - - gsl_vector *UtXb_new=gsl_vector_alloc (ni_test); - gsl_vector *UtXb_old=gsl_vector_alloc (ni_test); - - gsl_vector *z_hat=gsl_vector_alloc (ni_test); - gsl_vector *z=gsl_vector_alloc (ni_test); - gsl_vector *Utz=gsl_vector_alloc (ni_test); - - gsl_vector_memcpy (Utz, Uty); - - double logPost_new, logPost_old; - double logMHratio; - double mean_z=0.0; - - gsl_matrix_set_zero (Result_gamma); - gsl_vector_set_zero (Utu); - gsl_vector_set_zero (alpha_prime); - if (a_mode==13) { - pheno_mean=0.0; - } - - vector<pair<double, double> > beta_g; - for (size_t i=0; i<ns_test; i++) { - beta_g.push_back(make_pair(0.0, 0.0)); - } - - vector<size_t> rank_new, rank_old; - vector<double> beta_new, beta_old; - - vector<pair<size_t, double> > pos_loglr; - - time_start=clock(); - MatrixCalcLR (U, UtX, Utz, K_eval, l_min, l_max, n_region, pos_loglr); - time_Proposal=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - stable_sort (pos_loglr.begin(), pos_loglr.end(), comp_lr); - for (size_t i=0; i<ns_test; ++i) { - mapRank2pos[i]=pos_loglr[i].first; - } - - //calculate proposal distribution for gamma (unnormalized), and set up gsl_r and gsl_t - gsl_rng_env_setup(); - const gsl_rng_type * gslType; - gslType = gsl_rng_default; - if (randseed<0) - { - time_t rawtime; - time (&rawtime); - tm * ptm = gmtime (&rawtime); - - randseed = (unsigned) (ptm->tm_hour%24*3600+ptm->tm_min*60+ptm->tm_sec); - } - gsl_r = gsl_rng_alloc(gslType); - gsl_rng_set(gsl_r, randseed); - - double *p_gamma = new double[ns_test]; - CalcPgamma (p_gamma); - - gsl_t=gsl_ran_discrete_preproc (ns_test, p_gamma); - - //initial parameters - InitialMCMC (UtX, Utz, rank_old, cHyp_old, pos_loglr); -// if (fix_sigma>=0) { -// rho_max=1-fix_sigma; -// cHyp_old.h=fix_sigma/(1-cHyp_old.rho); -// } - - cHyp_initial=cHyp_old; - - if (cHyp_old.n_gamma==0 || cHyp_old.rho==0) { - logPost_old=CalcPosterior(Utz, K_eval, Utu_old, alpha_old, cHyp_old); - - beta_old.clear(); - for (size_t i=0; i<cHyp_old.n_gamma; ++i) { - beta_old.push_back(0); - } - } - else { - gsl_matrix *UtXgamma=gsl_matrix_alloc (ni_test, cHyp_old.n_gamma); - gsl_vector *beta=gsl_vector_alloc (cHyp_old.n_gamma); - SetXgamma (UtXgamma, UtX, rank_old); - logPost_old=CalcPosterior(UtXgamma, Utz, K_eval, UtXb_old, Utu_old, alpha_old, beta, cHyp_old); - - beta_old.clear(); - for (size_t i=0; i<beta->size; ++i) { - beta_old.push_back(gsl_vector_get(beta, i)); - } - gsl_matrix_free (UtXgamma); - gsl_vector_free (beta); - } - - //calculate centered z_hat, and pve - if (a_mode==13) { - time_start=clock(); - if (cHyp_old.n_gamma==0 || cHyp_old.rho==0) { - CalcCC_PVEnZ (U, Utu_old, z_hat, cHyp_old); - } - else { - CalcCC_PVEnZ (U, UtXb_old, Utu_old, z_hat, cHyp_old); - } - time_UtZ+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } - - //start MCMC - int accept; - size_t total_step=w_step+s_step; - size_t w=0, w_col, pos; - size_t repeat=0; - - for (size_t t=0; t<total_step; ++t) { - if (t%d_pace==0 || t==total_step-1) {ProgressBar ("Running MCMC ", t, total_step-1, (double)n_accept/(double)(t*n_mh+1));} -// if (t>10) {break;} - - if (a_mode==13) { - SampleZ (y, z_hat, z); - mean_z=CenterVector (z); - - time_start=clock(); - gsl_blas_dgemv (CblasTrans, 1.0, U, z, 0.0, Utz); - time_UtZ+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //First proposal - if (cHyp_old.n_gamma==0 || cHyp_old.rho==0) { - logPost_old=CalcPosterior(Utz, K_eval, Utu_old, alpha_old, cHyp_old); - beta_old.clear(); - for (size_t i=0; i<cHyp_old.n_gamma; ++i) { - beta_old.push_back(0); - } - } - else { - gsl_matrix *UtXgamma=gsl_matrix_alloc (ni_test, cHyp_old.n_gamma); - gsl_vector *beta=gsl_vector_alloc (cHyp_old.n_gamma); - SetXgamma (UtXgamma, UtX, rank_old); - logPost_old=CalcPosterior(UtXgamma, Utz, K_eval, UtXb_old, Utu_old, alpha_old, beta, cHyp_old); - - beta_old.clear(); - for (size_t i=0; i<beta->size; ++i) { - beta_old.push_back(gsl_vector_get(beta, i)); - } - gsl_matrix_free (UtXgamma); - gsl_vector_free (beta); - } - } - - //MH steps - for (size_t i=0; i<n_mh; ++i) { - if (gsl_rng_uniform(gsl_r)<0.33) {repeat = 1+gsl_rng_uniform_int(gsl_r, 20);} - else {repeat=1;} - - logMHratio=0.0; - logMHratio+=ProposeHnRho(cHyp_old, cHyp_new, repeat); - logMHratio+=ProposeGamma (rank_old, rank_new, p_gamma, cHyp_old, cHyp_new, repeat); - logMHratio+=ProposePi(cHyp_old, cHyp_new, repeat); - -// if (fix_sigma>=0) { -// cHyp_new.h=fix_sigma/(1-cHyp_new.rho); -// } - - if (cHyp_new.n_gamma==0 || cHyp_new.rho==0) { - logPost_new=CalcPosterior(Utz, K_eval, Utu_new, alpha_new, cHyp_new); - beta_new.clear(); - for (size_t i=0; i<cHyp_new.n_gamma; ++i) { - beta_new.push_back(0); - } - } - else { - gsl_matrix *UtXgamma=gsl_matrix_alloc (ni_test, cHyp_new.n_gamma); - gsl_vector *beta=gsl_vector_alloc (cHyp_new.n_gamma); - SetXgamma (UtXgamma, UtX, rank_new); - logPost_new=CalcPosterior(UtXgamma, Utz, K_eval, UtXb_new, Utu_new, alpha_new, beta, cHyp_new); - beta_new.clear(); - for (size_t i=0; i<beta->size; ++i) { - beta_new.push_back(gsl_vector_get(beta, i)); - } - gsl_matrix_free (UtXgamma); - gsl_vector_free (beta); - } - - logMHratio+=logPost_new-logPost_old; - - if (logMHratio>0 || log(gsl_rng_uniform(gsl_r))<logMHratio) {accept=1; n_accept++;} - else {accept=0;} - - if (accept==1) { - logPost_old=logPost_new; - rank_old.clear(); beta_old.clear(); - if (rank_new.size()!=0) { - for (size_t i=0; i<rank_new.size(); ++i) { - rank_old.push_back(rank_new[i]); - beta_old.push_back(beta_new[i]); - } - } - cHyp_old=cHyp_new; - gsl_vector_memcpy (alpha_old, alpha_new); - gsl_vector_memcpy (UtXb_old, UtXb_new); - gsl_vector_memcpy (Utu_old, Utu_new); - } - else {cHyp_new=cHyp_old;} - } - - //calculate z_hat, and pve - if (a_mode==13) { - time_start=clock(); - if (cHyp_old.n_gamma==0 || cHyp_old.rho==0) { - CalcCC_PVEnZ (U, Utu_old, z_hat, cHyp_old); - } - else { - CalcCC_PVEnZ (U, UtXb_old, Utu_old, z_hat, cHyp_old); - } - - //sample mu and update z hat - gsl_vector_sub (z, z_hat); - mean_z+=CenterVector(z); - mean_z+=gsl_ran_gaussian(gsl_r, sqrt(1.0/(double) ni_test) ); - - gsl_vector_add_constant (z_hat, mean_z); - - time_UtZ+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } - - //Save data - if (t<w_step) {continue;} - else { - if (t%r_pace==0) { - w_col=w%w_pace; - if (w_col==0) { - if (w==0) {WriteResult (0, Result_hyp, Result_gamma, w_col);} - else { - WriteResult (1, Result_hyp, Result_gamma, w_col); - gsl_matrix_set_zero (Result_hyp); - gsl_matrix_set_zero (Result_gamma); - } - } - - gsl_matrix_set (Result_hyp, w_col, 0, cHyp_old.h); - gsl_matrix_set (Result_hyp, w_col, 1, cHyp_old.pve); - gsl_matrix_set (Result_hyp, w_col, 2, cHyp_old.rho); - gsl_matrix_set (Result_hyp, w_col, 3, cHyp_old.pge); - gsl_matrix_set (Result_hyp, w_col, 4, cHyp_old.logp); - gsl_matrix_set (Result_hyp, w_col, 5, cHyp_old.n_gamma); - - for (size_t i=0; i<cHyp_old.n_gamma; ++i) { - pos=mapRank2pos[rank_old[i]]+1; - - gsl_matrix_set (Result_gamma, w_col, i, pos); - - beta_g[pos-1].first+=beta_old[i]; - beta_g[pos-1].second+=1.0; - } - - gsl_vector_add (alpha_prime, alpha_old); - gsl_vector_add (Utu, Utu_old); - - if (a_mode==13) { - pheno_mean+=mean_z; - } - - w++; - - } - - } - } - cout<<endl; - - w_col=w%w_pace; - WriteResult (1, Result_hyp, Result_gamma, w_col); - - gsl_matrix_free(Result_hyp); - gsl_matrix_free(Result_gamma); - - gsl_vector_free(z_hat); - gsl_vector_free(z); - gsl_vector_free(Utz); - gsl_vector_free(UtXb_new); - gsl_vector_free(UtXb_old); - gsl_vector_free(alpha_new); - gsl_vector_free(alpha_old); - gsl_vector_free(Utu_new); - gsl_vector_free(Utu_old); - - gsl_vector_scale (alpha_prime, 1.0/(double)w); - gsl_vector_scale (Utu, 1.0/(double)w); - if (a_mode==13) { - pheno_mean/=(double)w; - } - - gsl_vector *alpha=gsl_vector_alloc (ns_test); - gsl_blas_dgemv (CblasTrans, 1.0/(double)ns_test, UtX, alpha_prime, 0.0, alpha); - WriteParam (beta_g, alpha, w); - gsl_vector_free(alpha); - - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Utu, 0.0, alpha_prime); - WriteBV(alpha_prime); - - gsl_vector_free(alpha_prime); - gsl_vector_free(Utu); - - delete [] p_gamma; - beta_g.clear(); - - return; -} - - - -void BSLMM::RidgeR(const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *eval, const double lambda) -{ - gsl_vector *beta=gsl_vector_alloc (UtX->size2); - gsl_vector *H_eval=gsl_vector_alloc (Uty->size); - gsl_vector *bv=gsl_vector_alloc (Uty->size); - - gsl_vector_memcpy (H_eval, eval); - gsl_vector_scale (H_eval, lambda); - gsl_vector_add_constant (H_eval, 1.0); - - gsl_vector_memcpy (bv, Uty); - gsl_vector_div (bv, H_eval); - - gsl_blas_dgemv (CblasTrans, lambda/(double)UtX->size2, UtX, bv, 0.0, beta); - gsl_vector_add_constant (H_eval, -1.0); - gsl_vector_mul (H_eval, bv); - gsl_blas_dgemv (CblasNoTrans, 1.0, U, H_eval, 0.0, bv); - - WriteParam (beta); - WriteBV(bv); - - gsl_vector_free (H_eval); - gsl_vector_free (beta); - gsl_vector_free (bv); - - return; -} - - - - - - - - - - - - - - - - - -//below fits MCMC for rho=1 -void BSLMM::CalcXtX (const gsl_matrix *X, const gsl_vector *y, const size_t s_size, gsl_matrix *XtX, gsl_vector *Xty) -{ - time_t time_start=clock(); - gsl_matrix_const_view X_sub=gsl_matrix_const_submatrix(X, 0, 0, X->size1, s_size); - gsl_matrix_view XtX_sub=gsl_matrix_submatrix(XtX, 0, 0, s_size, s_size); - gsl_vector_view Xty_sub=gsl_vector_subvector(Xty, 0, s_size); - -#ifdef WITH_LAPACK - lapack_dgemm ((char *)"T", (char *)"N", 1.0, &X_sub.matrix, &X_sub.matrix, 0.0, &XtX_sub.matrix); -#else - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, &X_sub.matrix, &X_sub.matrix, 0.0, &XtX_sub.matrix); -#endif - gsl_blas_dgemv(CblasTrans, 1.0, &X_sub.matrix, y, 0.0, &Xty_sub.vector); - - time_Omega+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - return; -} - - -void BSLMM::SetXgamma (const gsl_matrix *X, const gsl_matrix *X_old, const gsl_matrix *XtX_old, const gsl_vector *Xty_old, const gsl_vector *y, const vector<size_t> &rank_old, const vector<size_t> &rank_new, gsl_matrix *X_new, gsl_matrix *XtX_new, gsl_vector *Xty_new) -{ - double d; - - //rank_old and rank_new are sorted already inside PorposeGamma - //calculate vectors rank_remove and rank_add - // size_t v_size=max(rank_old.size(), rank_new.size()); - //make sure that v_size is larger than repeat - size_t v_size=20; - vector<size_t> rank_remove(v_size), rank_add(v_size), rank_union(s_max+v_size); - vector<size_t>::iterator it; - - it=set_difference (rank_old.begin(), rank_old.end(), rank_new.begin(), rank_new.end(), rank_remove.begin()); - rank_remove.resize(it-rank_remove.begin()); - - it=set_difference (rank_new.begin(), rank_new.end(), rank_old.begin(), rank_old.end(), rank_add.begin()); - rank_add.resize(it-rank_add.begin()); - - it=set_union (rank_new.begin(), rank_new.end(), rank_old.begin(), rank_old.end(), rank_union.begin()); - rank_union.resize(it-rank_union.begin()); - - //map rank_remove and rank_add - map<size_t, int> mapRank2in_remove, mapRank2in_add; - for (size_t i=0; i<rank_remove.size(); i++) { - mapRank2in_remove[rank_remove[i]]=1; - } - for (size_t i=0; i<rank_add.size(); i++) { - mapRank2in_add[rank_add[i]]=1; - } - - //obtain the subset of matrix/vector - gsl_matrix_const_view Xold_sub=gsl_matrix_const_submatrix(X_old, 0, 0, X_old->size1, rank_old.size()); - gsl_matrix_const_view XtXold_sub=gsl_matrix_const_submatrix(XtX_old, 0, 0, rank_old.size(), rank_old.size()); - gsl_vector_const_view Xtyold_sub=gsl_vector_const_subvector(Xty_old, 0, rank_old.size()); - - gsl_matrix_view Xnew_sub=gsl_matrix_submatrix(X_new, 0, 0, X_new->size1, rank_new.size()); - gsl_matrix_view XtXnew_sub=gsl_matrix_submatrix(XtX_new, 0, 0, rank_new.size(), rank_new.size()); - gsl_vector_view Xtynew_sub=gsl_vector_subvector(Xty_new, 0, rank_new.size()); - - //get X_new and calculate XtX_new - /* - if (rank_remove.size()==0 && rank_add.size()==0) { - gsl_matrix_memcpy(&Xnew_sub.matrix, &Xold_sub.matrix); - gsl_matrix_memcpy(&XtXnew_sub.matrix, &XtXold_sub.matrix); - gsl_vector_memcpy(&Xtynew_sub.vector, &Xtyold_sub.vector); - } else { - gsl_matrix *X_temp=gsl_matrix_alloc(X_old->size1, rank_old.size()-rank_remove.size() ); - gsl_matrix *XtX_temp=gsl_matrix_alloc(X_temp->size2, X_temp->size2); - gsl_vector *Xty_temp=gsl_vector_alloc(X_temp->size2); - - if (rank_remove.size()==0) { - gsl_matrix_memcpy (X_temp, &Xold_sub.matrix); - gsl_matrix_memcpy (XtX_temp, &XtXold_sub.matrix); - gsl_vector_memcpy (Xty_temp, &Xtyold_sub.vector); - } else { - size_t i_temp=0, j_temp; - for (size_t i=0; i<rank_old.size(); i++) { - if (mapRank2in_remove.count(rank_old[i])!=0) {continue;} - gsl_vector_const_view Xold_col=gsl_matrix_const_column(X_old, i); - gsl_vector_view Xtemp_col=gsl_matrix_column(X_temp, i_temp); - gsl_vector_memcpy (&Xtemp_col.vector, &Xold_col.vector); - - d=gsl_vector_get (Xty_old, i); - gsl_vector_set (Xty_temp, i_temp, d); - - j_temp=i_temp; - for (size_t j=i; j<rank_old.size(); j++) { - if (mapRank2in_remove.count(rank_old[j])!=0) {continue;} - d=gsl_matrix_get (XtX_old, i, j); - gsl_matrix_set (XtX_temp, i_temp, j_temp, d); - if (i_temp!=j_temp) {gsl_matrix_set (XtX_temp, j_temp, i_temp, d);} - j_temp++; - } - i_temp++; - } - } - - if (rank_add.size()==0) { - gsl_matrix_memcpy (&Xnew_sub.matrix, X_temp); - gsl_matrix_memcpy (&XtXnew_sub.matrix, XtX_temp); - gsl_vector_memcpy (&Xtynew_sub.vector, Xty_temp); - } else { - gsl_matrix *X_add=gsl_matrix_alloc(X_old->size1, rank_add.size() ); - gsl_matrix *XtX_aa=gsl_matrix_alloc(X_add->size2, X_add->size2); - gsl_matrix *XtX_at=gsl_matrix_alloc(X_add->size2, X_temp->size2); - gsl_vector *Xty_add=gsl_vector_alloc(X_add->size2); - - //get X_add - SetXgamma (X_add, X, rank_add); - - //get t(X_add)X_add and t(X_add)X_temp - clock_t time_start=clock(); - - //somehow the lapack_dgemm does not work here - //#ifdef WITH_LAPACK - //lapack_dgemm ((char *)"T", (char *)"N", 1.0, X_add, X_add, 0.0, XtX_aa); - //lapack_dgemm ((char *)"T", (char *)"N", 1.0, X_add, X_temp, 0.0, XtX_at); - - //#else - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, X_add, X_add, 0.0, XtX_aa); - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, X_add, X_temp, 0.0, XtX_at); - //#endif - gsl_blas_dgemv(CblasTrans, 1.0, X_add, y, 0.0, Xty_add); - - time_Omega+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //save to X_new, XtX_new and Xty_new - size_t i_temp=0, j_temp, i_flag=0, j_flag=0; - for (size_t i=0; i<rank_new.size(); i++) { - if (mapRank2in_add.count(rank_new[i])!=0) {i_flag=1;} else {i_flag=0;} - gsl_vector_view Xnew_col=gsl_matrix_column(X_new, i); - if (i_flag==1) { - gsl_vector_view Xcopy_col=gsl_matrix_column(X_add, i-i_temp); - gsl_vector_memcpy (&Xnew_col.vector, &Xcopy_col.vector); - } else { - gsl_vector_view Xcopy_col=gsl_matrix_column(X_temp, i_temp); - gsl_vector_memcpy (&Xnew_col.vector, &Xcopy_col.vector); - } - - if (i_flag==1) { - d=gsl_vector_get (Xty_add, i-i_temp); - } else { - d=gsl_vector_get (Xty_temp, i_temp); - } - gsl_vector_set (Xty_new, i, d); - - j_temp=i_temp; - for (size_t j=i; j<rank_new.size(); j++) { - if (mapRank2in_add.count(rank_new[j])!=0) {j_flag=1;} else {j_flag=0;} - - if (i_flag==1 && j_flag==1) { - d=gsl_matrix_get(XtX_aa, i-i_temp, j-j_temp); - } else if (i_flag==1) { - d=gsl_matrix_get(XtX_at, i-i_temp, j_temp); - } else if (j_flag==1) { - d=gsl_matrix_get(XtX_at, j-j_temp, i_temp); - } else { - d=gsl_matrix_get(XtX_temp, i_temp, j_temp); - } - - gsl_matrix_set (XtX_new, i, j, d); - if (i!=j) {gsl_matrix_set (XtX_new, j, i, d);} - - if (j_flag==0) {j_temp++;} - } - if (i_flag==0) {i_temp++;} - } - - gsl_matrix_free(X_add); - gsl_matrix_free(XtX_aa); - gsl_matrix_free(XtX_at); - gsl_vector_free(Xty_add); - } - - gsl_matrix_free(X_temp); - gsl_matrix_free(XtX_temp); - gsl_vector_free(Xty_temp); - } - */ - - - if (rank_remove.size()==0 && rank_add.size()==0) { - gsl_matrix_memcpy(&Xnew_sub.matrix, &Xold_sub.matrix); - gsl_matrix_memcpy(&XtXnew_sub.matrix, &XtXold_sub.matrix); - gsl_vector_memcpy(&Xtynew_sub.vector, &Xtyold_sub.vector); - } else { - size_t i_old, j_old, i_new, j_new, i_add, j_add, i_flag, j_flag; - if (rank_add.size()==0) { - i_old=0; i_new=0; - for (size_t i=0; i<rank_union.size(); i++) { - if (mapRank2in_remove.count(rank_old[i_old])!=0) {i_old++; continue;} - - gsl_vector_view Xnew_col=gsl_matrix_column(X_new, i_new); - gsl_vector_const_view Xcopy_col=gsl_matrix_const_column(X_old, i_old); - gsl_vector_memcpy (&Xnew_col.vector, &Xcopy_col.vector); - - d=gsl_vector_get (Xty_old, i_old); - gsl_vector_set (Xty_new, i_new, d); - - j_old=i_old; j_new=i_new; - for (size_t j=i; j<rank_union.size(); j++) { - if (mapRank2in_remove.count(rank_old[j_old])!=0) {j_old++; continue;} - - d=gsl_matrix_get(XtX_old, i_old, j_old); - - gsl_matrix_set (XtX_new, i_new, j_new, d); - if (i_new!=j_new) {gsl_matrix_set (XtX_new, j_new, i_new, d);} - - j_old++; j_new++; - } - i_old++; i_new++; - } - } else { - gsl_matrix *X_add=gsl_matrix_alloc(X_old->size1, rank_add.size() ); - gsl_matrix *XtX_aa=gsl_matrix_alloc(X_add->size2, X_add->size2); - gsl_matrix *XtX_ao=gsl_matrix_alloc(X_add->size2, X_old->size2); - gsl_vector *Xty_add=gsl_vector_alloc(X_add->size2); - - //get X_add - SetXgamma (X_add, X, rank_add); - - //get t(X_add)X_add and t(X_add)X_temp - clock_t time_start=clock(); - - //somehow the lapack_dgemm does not work here - //#ifdef WITH_LAPACK - //lapack_dgemm ((char *)"T", (char *)"N", 1.0, X_add, X_add, 0.0, XtX_aa); - //lapack_dgemm ((char *)"T", (char *)"N", 1.0, X_add, X_temp, 0.0, XtX_at); - - //#else - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, X_add, X_add, 0.0, XtX_aa); - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, X_add, X_old, 0.0, XtX_ao); - //#endif - gsl_blas_dgemv(CblasTrans, 1.0, X_add, y, 0.0, Xty_add); - - time_Omega+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //save to X_new, XtX_new and Xty_new - i_old=0; i_new=0; i_add=0; - for (size_t i=0; i<rank_union.size(); i++) { - if (mapRank2in_remove.count(rank_old[i_old])!=0) {i_old++; continue;} - if (mapRank2in_add.count(rank_new[i_new])!=0) {i_flag=1;} else {i_flag=0;} - - gsl_vector_view Xnew_col=gsl_matrix_column(X_new, i_new); - if (i_flag==1) { - gsl_vector_view Xcopy_col=gsl_matrix_column(X_add, i_add); - gsl_vector_memcpy (&Xnew_col.vector, &Xcopy_col.vector); - } else { - gsl_vector_const_view Xcopy_col=gsl_matrix_const_column(X_old, i_old); - gsl_vector_memcpy (&Xnew_col.vector, &Xcopy_col.vector); - } - - if (i_flag==1) { - d=gsl_vector_get (Xty_add, i_add); - } else { - d=gsl_vector_get (Xty_old, i_old); - } - gsl_vector_set (Xty_new, i_new, d); - - j_old=i_old; j_new=i_new; j_add=i_add; - for (size_t j=i; j<rank_union.size(); j++) { - if (mapRank2in_remove.count(rank_old[j_old])!=0) {j_old++; continue;} - if (mapRank2in_add.count(rank_new[j_new])!=0) {j_flag=1;} else {j_flag=0;} - - if (i_flag==1 && j_flag==1) { - d=gsl_matrix_get(XtX_aa, i_add, j_add); - } else if (i_flag==1) { - d=gsl_matrix_get(XtX_ao, i_add, j_old); - } else if (j_flag==1) { - d=gsl_matrix_get(XtX_ao, j_add, i_old); - } else { - d=gsl_matrix_get(XtX_old, i_old, j_old); - } - - gsl_matrix_set (XtX_new, i_new, j_new, d); - if (i_new!=j_new) {gsl_matrix_set (XtX_new, j_new, i_new, d);} - - j_new++; if (j_flag==1) {j_add++;} else {j_old++;} - } - i_new++; if (i_flag==1) {i_add++;} else {i_old++;} - } - - gsl_matrix_free(X_add); - gsl_matrix_free(XtX_aa); - gsl_matrix_free(XtX_ao); - gsl_vector_free(Xty_add); - } - - } - - rank_remove.clear(); - rank_add.clear(); - rank_union.clear(); - mapRank2in_remove.clear(); - mapRank2in_add.clear(); - - return; -} - - -double BSLMM::CalcPosterior (const double yty, class HYPBSLMM &cHyp) -{ - double logpost=0.0; - - //for quantitative traits, calculate pve and pge - //pve and pge for case/control data are calculted in CalcCC_PVEnZ - if (a_mode==11) { - cHyp.pve=0.0; - cHyp.pge=1.0; - } - - //calculate likelihood - if (a_mode==11) {logpost-=0.5*(double)ni_test*log(yty);} - else {logpost-=0.5*yty;} - - logpost+=((double)cHyp.n_gamma-1.0)*cHyp.logp+((double)ns_test-(double)cHyp.n_gamma)*log(1-exp(cHyp.logp)); - - return logpost; -} - - -double BSLMM::CalcPosterior (const gsl_matrix *Xgamma, const gsl_matrix *XtX, const gsl_vector *Xty, const double yty, const size_t s_size, gsl_vector *Xb, gsl_vector *beta, class HYPBSLMM &cHyp) -{ - double sigma_a2=cHyp.h/( (1-cHyp.h)*exp(cHyp.logp)*(double)ns_test); - double logpost=0.0; - double d, P_yy=yty, logdet_O=0.0; - - gsl_matrix_const_view Xgamma_sub=gsl_matrix_const_submatrix (Xgamma, 0, 0, Xgamma->size1, s_size); - gsl_matrix_const_view XtX_sub=gsl_matrix_const_submatrix (XtX, 0, 0, s_size, s_size); - gsl_vector_const_view Xty_sub=gsl_vector_const_subvector (Xty, 0, s_size); - - gsl_matrix *Omega=gsl_matrix_alloc (s_size, s_size); - gsl_matrix *M_temp=gsl_matrix_alloc (s_size, s_size); - gsl_vector *beta_hat=gsl_vector_alloc (s_size); - gsl_vector *Xty_temp=gsl_vector_alloc (s_size); - - gsl_vector_memcpy (Xty_temp, &Xty_sub.vector); - - //calculate Omega - gsl_matrix_memcpy (Omega, &XtX_sub.matrix); - gsl_matrix_scale (Omega, sigma_a2); - gsl_matrix_set_identity (M_temp); - gsl_matrix_add (Omega, M_temp); - - //calculate beta_hat - logdet_O=CholeskySolve(Omega, Xty_temp, beta_hat); - gsl_vector_scale (beta_hat, sigma_a2); - - gsl_blas_ddot (Xty_temp, beta_hat, &d); - P_yy-=d; - - //sample tau - double tau=1.0; - if (a_mode==11) {tau =gsl_ran_gamma (gsl_r, (double)ni_test/2.0, 2.0/P_yy); } - - //sample beta - for (size_t i=0; i<s_size; i++) - { - d=gsl_ran_gaussian(gsl_r, 1); - gsl_vector_set(beta, i, d); - } - gsl_vector_view beta_sub=gsl_vector_subvector(beta, 0, s_size); - gsl_blas_dtrsv(CblasUpper, CblasNoTrans, CblasNonUnit, Omega, &beta_sub.vector); - - //it compuates inv(L^T(Omega)) %*% beta; - gsl_vector_scale(&beta_sub.vector, sqrt(sigma_a2/tau)); - gsl_vector_add(&beta_sub.vector, beta_hat); - gsl_blas_dgemv (CblasNoTrans, 1.0, &Xgamma_sub.matrix, &beta_sub.vector, 0.0, Xb); - - //for quantitative traits, calculate pve and pge - if (a_mode==11) { - gsl_blas_ddot (Xb, Xb, &d); - cHyp.pve=d/(double)ni_test; - cHyp.pve/=cHyp.pve+1.0/tau; - cHyp.pge=1.0; - } - - logpost=-0.5*logdet_O; - if (a_mode==11) {logpost-=0.5*(double)ni_test*log(P_yy);} - else {logpost-=0.5*P_yy;} - - logpost+=((double)cHyp.n_gamma-1.0)*cHyp.logp+((double)ns_test-(double)cHyp.n_gamma)*log(1.0-exp(cHyp.logp)); - - gsl_matrix_free (Omega); - gsl_matrix_free (M_temp); - gsl_vector_free (beta_hat); - gsl_vector_free (Xty_temp); - - return logpost; -} - - - -//calculate pve and pge, and calculate z_hat for case-control data -void BSLMM::CalcCC_PVEnZ (gsl_vector *z_hat, class HYPBSLMM &cHyp) -{ - gsl_vector_set_zero(z_hat); - cHyp.pve=0.0; - cHyp.pge=1.0; - return; -} - - -//calculate pve and pge, and calculate z_hat for case-control data -void BSLMM::CalcCC_PVEnZ (const gsl_vector *Xb, gsl_vector *z_hat, class HYPBSLMM &cHyp) -{ - double d; - - gsl_blas_ddot (Xb, Xb, &d); - cHyp.pve=d/(double)ni_test; - cHyp.pve/=cHyp.pve+1.0; - cHyp.pge=1.0; - - gsl_vector_memcpy (z_hat, Xb); - - return; -} - - - -//if a_mode==13, then run probit model -void BSLMM::MCMC (const gsl_matrix *X, const gsl_vector *y) { - clock_t time_start; - double time_set=0, time_post=0; - - class HYPBSLMM cHyp_old, cHyp_new; - - gsl_matrix *Result_hyp=gsl_matrix_alloc (w_pace, 6); - gsl_matrix *Result_gamma=gsl_matrix_alloc (w_pace, s_max); - - gsl_vector *Xb_new=gsl_vector_alloc (ni_test); - gsl_vector *Xb_old=gsl_vector_alloc (ni_test); - gsl_vector *z_hat=gsl_vector_alloc (ni_test); - gsl_vector *z=gsl_vector_alloc (ni_test); - - gsl_matrix *Xgamma_old=gsl_matrix_alloc (ni_test, s_max); - gsl_matrix *XtX_old=gsl_matrix_alloc (s_max, s_max); - gsl_vector *Xtz_old=gsl_vector_alloc (s_max); - gsl_vector *beta_old=gsl_vector_alloc (s_max); - - gsl_matrix *Xgamma_new=gsl_matrix_alloc (ni_test, s_max); - gsl_matrix *XtX_new=gsl_matrix_alloc (s_max, s_max); - gsl_vector *Xtz_new=gsl_vector_alloc (s_max); - gsl_vector *beta_new=gsl_vector_alloc (s_max); - - double ztz=0.0; - gsl_vector_memcpy (z, y); - //for quantitative traits, y is centered already in gemma.cpp, but just in case - double mean_z=CenterVector (z); - gsl_blas_ddot(z, z, &ztz); - - double logPost_new, logPost_old; - double logMHratio; - - gsl_matrix_set_zero (Result_gamma); - if (a_mode==13) { - pheno_mean=0.0; - } - - vector<pair<double, double> > beta_g; - for (size_t i=0; i<ns_test; i++) { - beta_g.push_back(make_pair(0.0, 0.0)); - } - - vector<size_t> rank_new, rank_old; - vector<pair<size_t, double> > pos_loglr; - - time_start=clock(); - MatrixCalcLmLR (X, z, pos_loglr); - time_Proposal=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - stable_sort (pos_loglr.begin(), pos_loglr.end(), comp_lr); - for (size_t i=0; i<ns_test; ++i) { - mapRank2pos[i]=pos_loglr[i].first; - } - - //calculate proposal distribution for gamma (unnormalized), and set up gsl_r and gsl_t - gsl_rng_env_setup(); - const gsl_rng_type * gslType; - gslType = gsl_rng_default; - if (randseed<0) - { - time_t rawtime; - time (&rawtime); - tm * ptm = gmtime (&rawtime); - - randseed = (unsigned) (ptm->tm_hour%24*3600+ptm->tm_min*60+ptm->tm_sec); - } - gsl_r = gsl_rng_alloc(gslType); - gsl_rng_set(gsl_r, randseed); - - double *p_gamma = new double[ns_test]; - CalcPgamma (p_gamma); - - gsl_t=gsl_ran_discrete_preproc (ns_test, p_gamma); - - //initial parameters - InitialMCMC (X, z, rank_old, cHyp_old, pos_loglr); - - cHyp_initial=cHyp_old; - - if (cHyp_old.n_gamma==0) { - logPost_old=CalcPosterior (ztz, cHyp_old); - } - else { - SetXgamma (Xgamma_old, X, rank_old); - CalcXtX (Xgamma_old, z, rank_old.size(), XtX_old, Xtz_old); - logPost_old=CalcPosterior (Xgamma_old, XtX_old, Xtz_old, ztz, rank_old.size(), Xb_old, beta_old, cHyp_old); - } - - //calculate centered z_hat, and pve - if (a_mode==13) { - if (cHyp_old.n_gamma==0) { - CalcCC_PVEnZ (z_hat, cHyp_old); - } - else { - CalcCC_PVEnZ (Xb_old, z_hat, cHyp_old); - } - } - - //start MCMC - int accept; - size_t total_step=w_step+s_step; - size_t w=0, w_col, pos; - size_t repeat=0; - - for (size_t t=0; t<total_step; ++t) { - if (t%d_pace==0 || t==total_step-1) {ProgressBar ("Running MCMC ", t, total_step-1, (double)n_accept/(double)(t*n_mh+1));} -// if (t>10) {break;} - if (a_mode==13) { - SampleZ (y, z_hat, z); - mean_z=CenterVector (z); - gsl_blas_ddot(z,z,&ztz); - - //First proposal - if (cHyp_old.n_gamma==0) { - logPost_old=CalcPosterior (ztz, cHyp_old); - } else { - gsl_matrix_view Xold_sub=gsl_matrix_submatrix(Xgamma_old, 0, 0, ni_test, rank_old.size()); - gsl_vector_view Xtz_sub=gsl_vector_subvector(Xtz_old, 0, rank_old.size()); - gsl_blas_dgemv (CblasTrans, 1.0, &Xold_sub.matrix, z, 0.0, &Xtz_sub.vector); - logPost_old=CalcPosterior (Xgamma_old, XtX_old, Xtz_old, ztz, rank_old.size(), Xb_old, beta_old, cHyp_old); - } - } - - //MH steps - for (size_t i=0; i<n_mh; ++i) { - if (gsl_rng_uniform(gsl_r)<0.33) {repeat = 1+gsl_rng_uniform_int(gsl_r, 20);} - else {repeat=1;} - - logMHratio=0.0; - logMHratio+=ProposeHnRho(cHyp_old, cHyp_new, repeat); - logMHratio+=ProposeGamma (rank_old, rank_new, p_gamma, cHyp_old, cHyp_new, repeat); - logMHratio+=ProposePi(cHyp_old, cHyp_new, repeat); - - if (cHyp_new.n_gamma==0) { - logPost_new=CalcPosterior (ztz, cHyp_new); - } else { - //this if makes sure that rank_old.size()==rank_remove.size() does not happen - if (cHyp_new.n_gamma<=20 || cHyp_old.n_gamma<=20) { - time_start=clock(); - SetXgamma (Xgamma_new, X, rank_new); - CalcXtX (Xgamma_new, z, rank_new.size(), XtX_new, Xtz_new); - time_set+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } else { - time_start=clock(); - SetXgamma (X, Xgamma_old, XtX_old, Xtz_old, z, rank_old, rank_new, Xgamma_new, XtX_new, Xtz_new); - time_set+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } - time_start=clock(); - logPost_new=CalcPosterior (Xgamma_new, XtX_new, Xtz_new, ztz, rank_new.size(), Xb_new, beta_new, cHyp_new); - time_post+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } - logMHratio+=logPost_new-logPost_old; - - if (logMHratio>0 || log(gsl_rng_uniform(gsl_r))<logMHratio) {accept=1; n_accept++;} - else {accept=0;} - - //cout<<rank_new.size()<<"\t"<<rank_old.size()<<"\t"<<logPost_new<<"\t"<<logPost_old<<endl; - if (accept==1) { - logPost_old=logPost_new; - cHyp_old=cHyp_new; - gsl_vector_memcpy (Xb_old, Xb_new); - - rank_old.clear(); - if (rank_new.size()!=0) { - for (size_t i=0; i<rank_new.size(); ++i) { - rank_old.push_back(rank_new[i]); - } - - gsl_matrix_view Xold_sub=gsl_matrix_submatrix(Xgamma_old, 0, 0, ni_test, rank_new.size()); - gsl_matrix_view XtXold_sub=gsl_matrix_submatrix(XtX_old, 0, 0, rank_new.size(), rank_new.size()); - gsl_vector_view Xtzold_sub=gsl_vector_subvector(Xtz_old, 0, rank_new.size()); - gsl_vector_view betaold_sub=gsl_vector_subvector(beta_old, 0, rank_new.size()); - - gsl_matrix_view Xnew_sub=gsl_matrix_submatrix(Xgamma_new, 0, 0, ni_test, rank_new.size()); - gsl_matrix_view XtXnew_sub=gsl_matrix_submatrix(XtX_new, 0, 0, rank_new.size(), rank_new.size()); - gsl_vector_view Xtznew_sub=gsl_vector_subvector(Xtz_new, 0, rank_new.size()); - gsl_vector_view betanew_sub=gsl_vector_subvector(beta_new, 0, rank_new.size()); - - gsl_matrix_memcpy(&Xold_sub.matrix, &Xnew_sub.matrix); - gsl_matrix_memcpy(&XtXold_sub.matrix, &XtXnew_sub.matrix); - gsl_vector_memcpy(&Xtzold_sub.vector, &Xtznew_sub.vector); - gsl_vector_memcpy(&betaold_sub.vector, &betanew_sub.vector); - } - } else { - cHyp_new=cHyp_old; - } - - } - - //calculate z_hat, and pve - if (a_mode==13) { - if (cHyp_old.n_gamma==0) { - CalcCC_PVEnZ (z_hat, cHyp_old); - } - else { - CalcCC_PVEnZ (Xb_old, z_hat, cHyp_old); - } - - //sample mu and update z hat - gsl_vector_sub (z, z_hat); - mean_z+=CenterVector(z); - mean_z+=gsl_ran_gaussian(gsl_r, sqrt(1.0/(double) ni_test) ); - - gsl_vector_add_constant (z_hat, mean_z); - } - - //Save data - if (t<w_step) {continue;} - else { - if (t%r_pace==0) { - w_col=w%w_pace; - if (w_col==0) { - if (w==0) {WriteResult (0, Result_hyp, Result_gamma, w_col);} - else { - WriteResult (1, Result_hyp, Result_gamma, w_col); - gsl_matrix_set_zero (Result_hyp); - gsl_matrix_set_zero (Result_gamma); - } - } - - gsl_matrix_set (Result_hyp, w_col, 0, cHyp_old.h); - gsl_matrix_set (Result_hyp, w_col, 1, cHyp_old.pve); - gsl_matrix_set (Result_hyp, w_col, 2, cHyp_old.rho); - gsl_matrix_set (Result_hyp, w_col, 3, cHyp_old.pge); - gsl_matrix_set (Result_hyp, w_col, 4, cHyp_old.logp); - gsl_matrix_set (Result_hyp, w_col, 5, cHyp_old.n_gamma); - - for (size_t i=0; i<cHyp_old.n_gamma; ++i) { - pos=mapRank2pos[rank_old[i]]+1; - - gsl_matrix_set (Result_gamma, w_col, i, pos); - - beta_g[pos-1].first+=gsl_vector_get(beta_old, i); - beta_g[pos-1].second+=1.0; - } - - if (a_mode==13) { - pheno_mean+=mean_z; - } - - w++; - - } - - } - } - cout<<endl; - - cout<<"time on selecting Xgamma: "<<time_set<<endl; - cout<<"time on calculating posterior: "<<time_post<<endl; - - w_col=w%w_pace; - WriteResult (1, Result_hyp, Result_gamma, w_col); - - gsl_vector *alpha=gsl_vector_alloc (ns_test); - gsl_vector_set_zero (alpha); - WriteParam (beta_g, alpha, w); - gsl_vector_free(alpha); - - gsl_matrix_free(Result_hyp); - gsl_matrix_free(Result_gamma); - - gsl_vector_free(z_hat); - gsl_vector_free(z); - gsl_vector_free(Xb_new); - gsl_vector_free(Xb_old); - - gsl_matrix_free(Xgamma_old); - gsl_matrix_free(XtX_old); - gsl_vector_free(Xtz_old); - gsl_vector_free(beta_old); - - gsl_matrix_free(Xgamma_new); - gsl_matrix_free(XtX_new); - gsl_vector_free(Xtz_new); - gsl_vector_free(beta_new); - - delete [] p_gamma; - beta_g.clear(); - - return; -} diff --git a/bslmm.h b/bslmm.h deleted file mode 100644 index 8b5edc7..0000000 --- a/bslmm.h +++ /dev/null @@ -1,146 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - - -#ifndef __BSLMM_H__ -#define __BSLMM_H__ - -#include <vector> -#include <map> -#include <gsl/gsl_rng.h> -#include <gsl/gsl_randist.h> - -#ifdef FORCE_FLOAT -#include "param_float.h" -#else -#include "param.h" -#endif - - -using namespace std; - - - - - - -class BSLMM { - -public: - // IO related parameters - int a_mode; - size_t d_pace; - - string file_bfile; - string file_geno; - string file_out; - string path_out; - - // LMM related parameters - double l_min; - double l_max; - size_t n_region; - double pve_null; - double pheno_mean; - - // BSLMM MCMC related parameters - double h_min, h_max, h_scale; //priors for h - double rho_min, rho_max, rho_scale; //priors for rho - double logp_min, logp_max, logp_scale; //priors for log(pi) - size_t s_min, s_max; //minimum and maximum number of gammas - size_t w_step; //number of warm up/burn in iterations - size_t s_step; //number of sampling iterations - size_t r_pace; //record pace - size_t w_pace; //write pace - size_t n_accept; //number of acceptance - size_t n_mh; //number of MH steps within each iteration - double geo_mean; //mean of the geometric distribution - long int randseed; - double trace_G; - - HYPBSLMM cHyp_initial; - - // Summary statistics - size_t ni_total, ns_total; //number of total individuals and snps - size_t ni_test, ns_test; //number of individuals and snps used for analysis - size_t n_cvt; //number of covariates - double time_UtZ; - double time_Omega; //time spent on optimization iterations - double time_Proposal; //time spent on constructing the proposal distribution for gamma (i.e. lmm or lm analysis) - vector<int> indicator_idv; //indicator for individuals (phenotypes), 0 missing, 1 available for analysis - vector<int> indicator_snp; //sequence indicator for SNPs: 0 ignored because of (a) maf, (b) miss, (c) non-poly; 1 available for analysis - - vector<SNPINFO> snpInfo; //record SNP information - - // Not included in PARAM - gsl_rng *gsl_r; - gsl_ran_discrete_t *gsl_t; - map<size_t, size_t> mapRank2pos; - - // Main Functions - void CopyFromParam (PARAM &cPar); - void CopyToParam (PARAM &cPar); - - void RidgeR(const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *eval, const double lambda); - - void MCMC (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, const gsl_vector *y); - void WriteLog (); - void WriteLR (); - void WriteBV (const gsl_vector *bv); - void WriteParam (vector<pair<double, double> > &beta_g, const gsl_vector *alpha, const size_t w); - void WriteParam (const gsl_vector *alpha); - void WriteResult (const int flag, const gsl_matrix *Result_hyp, const gsl_matrix *Result_gamma, const size_t w_col); - - //Subfunctions inside MCMC - void CalcPgamma (double *p_gammar); - - double CalcPveLM (const gsl_matrix *UtXgamma, const gsl_vector *Uty, const double sigma_a2); - void InitialMCMC (const gsl_matrix *UtX, const gsl_vector *Uty, vector<size_t> &rank_old, class HYPBSLMM &cHyp, vector<pair<size_t, double> > &pos_loglr); - double CalcPosterior (const gsl_vector *Uty, const gsl_vector *K_eval, gsl_vector *Utu, gsl_vector *alpha_prime, class HYPBSLMM &cHyp); - double CalcPosterior (const gsl_matrix *UtXgamma, const gsl_vector *Uty, const gsl_vector *K_eval, gsl_vector *UtXb, gsl_vector *Utu, gsl_vector *alpha_prime, gsl_vector *beta, class HYPBSLMM &cHyp); - void CalcCC_PVEnZ (const gsl_matrix *U, const gsl_vector *Utu, gsl_vector *z_hat, class HYPBSLMM &cHyp); - void CalcCC_PVEnZ (const gsl_matrix *U, const gsl_vector *UtXb, const gsl_vector *Utu, gsl_vector *z_hat, class HYPBSLMM &cHyp); - double CalcREMLE (const gsl_matrix *Utw, const gsl_vector *Uty, const gsl_vector *K_eval); - double CalcLR (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, vector<pair<size_t, double> > &loglr_sort); //calculate the maximum marginal likelihood ratio for each analyzed SNPs with gemma, use it to rank SNPs - void SampleZ (const gsl_vector *y, const gsl_vector *z_hat, gsl_vector *z); - double ProposeHnRho (const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat); - double ProposePi (const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat); - double ProposeGamma (const vector<size_t> &rank_old, vector<size_t> &rank_new, const double *p_gamma, const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat); - void SetXgamma (gsl_matrix *Xgamma, const gsl_matrix *X, vector<size_t> &rank); - - void CalcXtX (const gsl_matrix *X_new, const gsl_vector *y, const size_t s_size, gsl_matrix *XtX_new, gsl_vector *Xty_new); - void SetXgamma (const gsl_matrix *X, const gsl_matrix *X_old, const gsl_matrix *XtX_old, const gsl_vector *Xty_old, const gsl_vector *y, const vector<size_t> &rank_old, const vector<size_t> &rank_new, gsl_matrix *X_new, gsl_matrix *XtX_new, gsl_vector *Xty_new); - double CalcPosterior (const double yty, class HYPBSLMM &cHyp); - double CalcPosterior (const gsl_matrix *Xgamma, const gsl_matrix *XtX, const gsl_vector *Xty, const double yty, const size_t s_size, gsl_vector *Xb, gsl_vector *beta, class HYPBSLMM &cHyp); - void CalcCC_PVEnZ (gsl_vector *z_hat, class HYPBSLMM &cHyp); - void CalcCC_PVEnZ (const gsl_vector *Xb, gsl_vector *z_hat, class HYPBSLMM &cHyp); - void MCMC (const gsl_matrix *X, const gsl_vector *y); - - //utility functions -// double vec_sum (gsl_vector *v); -// void vec_center (gsl_vector *v); -// double calc_var (gsl_vector *v); -// void calc_sigma (MCMC &cMcmc); -// bool comp_lr (pair<size_t, double> a, pair<size_t, double> b); -}; - - - -#endif - - diff --git a/gemma b/gemma deleted file mode 100755 index 6734240..0000000 --- a/gemma +++ /dev/null Binary files differdiff --git a/gemma.cpp b/gemma.cpp deleted file mode 100644 index b8693a8..0000000 --- a/gemma.cpp +++ /dev/null @@ -1,1864 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#include <iostream> -#include <fstream> -#include <string> -#include <cstring> -#include <sys/stat.h> -#include <ctime> -#include <cmath> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" -#include "gsl/gsl_eigen.h" -#include "gsl/gsl_cdf.h" - -#include "lapack.h" //for functions EigenDecomp - -#ifdef FORCE_FLOAT -#include "io_float.h" //for function ReadFile_kin -#include "gemma_float.h" -#include "vc_float.h" -#include "lm_float.h" //for LM class -#include "bslmm_float.h" //for BSLMM class -#include "lmm_float.h" //for LMM class, and functions CalcLambda, CalcPve, CalcVgVe -#include "mvlmm_float.h" //for MVLMM class -#include "prdt_float.h" //for PRDT class -#include "mathfunc_float.h" //for a few functions -#else -#include "io.h" -#include "gemma.h" -#include "vc.h" -#include "lm.h" -#include "bslmm.h" -#include "lmm.h" -#include "mvlmm.h" -#include "prdt.h" -#include "mathfunc.h" -#endif - - -using namespace std; - - - -GEMMA::GEMMA(void): -version("0.95alpha"), date("08/08/2014"), year("2011") -{} - -void GEMMA::PrintHeader (void) -{ - cout<<endl; - cout<<"*********************************************************"<<endl; - cout<<" Genome-wide Efficient Mixed Model Association (GEMMA) "<<endl; - cout<<" Version "<<version<<", "<<date<<" "<<endl; - cout<<" Visit "<<endl; - cout<<" http://stephenslab.uchicago.edu/software.html "<<endl; - cout<<" http://home.uchicago.edu/~xz7/software.html "<<endl; - cout<<" For Possible Updates "<<endl; - cout<<" (C) "<<year<<" Xiang Zhou "<<endl; - cout<<" GNU General Public License "<<endl; - cout<<" For Help, Type ./gemma -h "<<endl; - cout<<"*********************************************************"<<endl; - cout<<endl; - - return; -} - - -void GEMMA::PrintLicense (void) -{ - cout<<endl; - cout<<"The Software Is Distributed Under GNU General Public License, But May Also Require The Following Notifications."<<endl; - cout<<endl; - - cout<<"Including Lapack Routines In The Software May Require The Following Notification:"<<endl; - cout<<"Copyright (c) 1992-2010 The University of Tennessee and The University of Tennessee Research Foundation. All rights reserved."<<endl; - cout<<"Copyright (c) 2000-2010 The University of California Berkeley. All rights reserved."<<endl; - cout<<"Copyright (c) 2006-2010 The University of Colorado Denver. All rights reserved."<<endl; - cout<<endl; - - cout<<"$COPYRIGHT$"<<endl; - cout<<"Additional copyrights may follow"<<endl; - cout<<"$HEADER$"<<endl; - cout<<"Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:"<<endl; - cout<<"- Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer."<<endl; - cout<<"- Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer listed in this license in the documentation and/or other materials provided with the distribution."<<endl; - cout<<"- Neither the name of the copyright holders nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission."<<endl; - cout<<"The copyright holders provide no reassurances that the source code provided does not infringe any patent, copyright, or any other " - <<"intellectual property rights of third parties. The copyright holders disclaim any liability to any recipient for claims brought against " - <<"recipient by any third party for infringement of that parties intellectual property rights. "<<endl; - cout<<"THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT " - <<"LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT " - <<"OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT " - <<"LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY " - <<"THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE " - <<"OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE."<<endl; - cout<<endl; - - - - return; -} - - - -void GEMMA::PrintHelp(size_t option) -{ - if (option==0) { - cout<<endl; - cout<<" GEMMA version "<<version<<", released on "<<date<<endl; - cout<<" implemented by Xiang Zhou"<<endl; - cout<<endl; - cout<<" type ./gemma -h [num] for detailed helps"<<endl; - cout<<" options: " << endl; - cout<<" 1: quick guide"<<endl; - cout<<" 2: file I/O related"<<endl; - cout<<" 3: SNP QC"<<endl; - cout<<" 4: calculate relatedness matrix"<<endl; - cout<<" 5: perform eigen decomposition"<<endl; - cout<<" 6: perform variance component estiamtion"<<endl; - cout<<" 7: fit a linear model"<<endl; - cout<<" 8: fit a linear mixed model"<<endl; - cout<<" 9: fit a multivariate linear mixed model"<<endl; - cout<<" 10: fit a Bayesian sparse linear mixed model"<<endl; - cout<<" 11: obtain predicted values"<<endl; - cout<<" 12: note"<<endl; - cout<<endl; - } - - if (option==1) { - cout<<" QUICK GUIDE" << endl; - cout<<" to generate a relatedness matrix: "<<endl; - cout<<" ./gemma -bfile [prefix] -gk [num] -o [prefix]"<<endl; - cout<<" ./gemma -g [filename] -p [filename] -gk [num] -o [prefix]"<<endl; - cout<<" to perform eigen decomposition of the relatedness matrix: "<<endl; - cout<<" ./gemma -bfile [prefix] -k [filename] -eigen -o [prefix]"<<endl; - cout<<" ./gemma -g [filename] -p [filename] -k [filename] -eigen -o [prefix]"<<endl; - cout<<" to estimate variance components: "<<endl; - cout<<" ./gemma -bfile [prefix] -k [filename] -vc -o [prefix]"<<endl; - cout<<" ./gemma -p [filename] -k [filename] -vc -o [prefix]"<<endl; - cout<<" ./gemma -bfile [prefix] -mk [filename] -vc -o [prefix]"<<endl; - cout<<" ./gemma -p [filename] -mk [filename] -vc -o [prefix]"<<endl; - cout<<" to fit a linear mixed model: "<<endl; - cout<<" ./gemma -bfile [prefix] -k [filename] -lmm [num] -o [prefix]"<<endl; - cout<<" ./gemma -g [filename] -p [filename] -a [filename] -k [filename] -lmm [num] -o [prefix]"<<endl; - cout<<" to fit a multivariate linear mixed model: "<<endl; - cout<<" ./gemma -bfile [prefix] -k [filename] -lmm [num] -n [num1] [num2] -o [prefix]"<<endl; - cout<<" ./gemma -g [filename] -p [filename] -a [filename] -k [filename] -lmm [num] -n [num1] [num2] -o [prefix]"<<endl; - cout<<" to fit a Bayesian sparse linear mixed model: "<<endl; - cout<<" ./gemma -bfile [prefix] -bslmm [num] -o [prefix]"<<endl; - cout<<" ./gemma -g [filename] -p [filename] -a [filename] -bslmm [num] -o [prefix]"<<endl; - cout<<" to obtain predicted values: "<<endl; - cout<<" ./gemma -bfile [prefix] -epm [filename] -emu [filename] -ebv [filename] -k [filename] -predict [num] -o [prefix]"<<endl; - cout<<" ./gemma -g [filename] -p [filename] -epm [filename] -emu [filename] -ebv [filename] -k [filename] -predict [num] -o [prefix]"<<endl; - cout<<endl; - } - - if (option==2) { - cout<<" FILE I/O RELATED OPTIONS" << endl; - cout<<" -bfile [prefix] "<<" specify input PLINK binary ped file prefix."<<endl; - cout<<" requires: *.fam, *.bim and *.bed files"<<endl; - cout<<" missing value: -9"<<endl; - cout<<" -g [filename] "<<" specify input BIMBAM mean genotype file name"<<endl; - cout<<" format: rs#1, allele0, allele1, genotype for individual 1, genotype for individual 2, ..."<<endl; - cout<<" rs#2, allele0, allele1, genotype for individual 1, genotype for individual 2, ..."<<endl; - cout<<" ..."<<endl; - cout<<" missing value: NA"<<endl; - cout<<" -p [filename] "<<" specify input BIMBAM phenotype file name"<<endl; - cout<<" format: phenotype for individual 1"<<endl; - cout<<" phenotype for individual 2"<<endl; - cout<<" ..."<<endl; - cout<<" missing value: NA"<<endl; - cout<<" -a [filename] "<<" specify input BIMBAM SNP annotation file name (optional)"<<endl; - cout<<" format: rs#1, base_position, chr_number"<<endl; - cout<<" rs#2, base_position, chr_number"<<endl; - cout<<" ..."<<endl; - cout<<" -k [filename] "<<" specify input kinship/relatedness matrix file name"<<endl; - cout<<" -mk [filename] "<<" specify input file which contains a list of kinship/relatedness matrices"<<endl; - cout<<" -u [filename] "<<" specify input file containing the eigen vectors of the kinship/relatedness matrix"<<endl; - cout<<" -d [filename] "<<" specify input file containing the eigen values of the kinship/relatedness matrix"<<endl; - cout<<" -c [filename] "<<" specify input covariates file name (optional)"<<endl; - cout<<" format: covariate 1 for individual 1, ... , covariate c for individual 1"<<endl; - cout<<" covariate 1 for individual 2, ... , covariate c for individual 2"<<endl; - cout<<" ..."<<endl; - cout<<" missing value: NA"<<endl; - cout<<" note: the intercept (a column of 1s) may need to be included"<<endl; - cout<<" -epm [filename] "<<" specify input estimated parameter file name"<<endl; - cout<<" -en [n1] [n2] [n3] [n4] "<<" specify values for the input estimated parameter file (with a header)"<<endl; - cout<<" options: n1: rs column number"<<endl; - cout<<" n2: estimated alpha column number (0 to ignore)"<<endl; - cout<<" n3: estimated beta column number (0 to ignore)"<<endl; - cout<<" n4: estimated gamma column number (0 to ignore)"<<endl; - cout<<" default: 2 4 5 6 if -ebv is not specified; 2 0 5 6 if -ebv is specified"<<endl; - cout<<" -ebv [filename] "<<" specify input estimated random effect (breeding value) file name"<<endl; - cout<<" format: value for individual 1"<<endl; - cout<<" value for individual 2"<<endl; - cout<<" ..."<<endl; - cout<<" missing value: NA"<<endl; - cout<<" -emu [filename] "<<" specify input log file name containing estimated mean"<<endl; - cout<<" -mu [num] "<<" specify input estimated mean value"<<endl; - cout<<" -gene [filename] "<<" specify input gene expression file name"<<endl; - cout<<" format: header"<<endl; - cout<<" gene1, count for individual 1, count for individual 2, ..."<<endl; - cout<<" gene2, count for individual 1, count for individual 2, ..."<<endl; - cout<<" ..."<<endl; - cout<<" missing value: not allowed"<<endl; - cout<<" -r [filename] "<<" specify input total read count file name"<<endl; - cout<<" format: total read count for individual 1"<<endl; - cout<<" total read count for individual 2"<<endl; - cout<<" ..."<<endl; - cout<<" missing value: NA"<<endl; - cout<<" -snps [filename] "<<" specify input snps file name to only analyze a certain set of snps"<<endl; - cout<<" format: rs#1"<<endl; - cout<<" rs#2"<<endl; - cout<<" ..."<<endl; - cout<<" missing value: NA"<<endl; - cout<<" -silence "<<" silent terminal display"<<endl; - cout<<" -km [num] "<<" specify input kinship/relatedness file type (default 1)."<<endl; - cout<<" options: 1: \"n by n matrix\" format"<<endl; - cout<<" 2: \"id id value\" format"<<endl; - cout<<" -n [num] "<<" specify phenotype column in the phenotype/*.fam file (optional; default 1)"<<endl; - cout<<" -pace [num] "<<" specify terminal display update pace (default 100000 SNPs or 100000 iterations)."<<endl; - cout<<" -outdir [path] "<<" specify output directory path (default \"./output/\")"<<endl; - cout<<" -o [prefix] "<<" specify output file prefix (default \"result\")"<<endl; - cout<<" output: prefix.cXX.txt or prefix.sXX.txt from kinship/relatedness matrix estimation"<<endl; - cout<<" output: prefix.assoc.txt and prefix.log.txt form association tests"<<endl; - cout<<endl; - } - - if (option==3) { - cout<<" SNP QC OPTIONS" << endl; - cout<<" -miss [num] "<<" specify missingness threshold (default 0.05)" << endl; - cout<<" -maf [num] "<<" specify minor allele frequency threshold (default 0.01)" << endl; - cout<<" -hwe [num] "<<" specify HWE test p value threshold (default 0; no test)" << endl; - cout<<" -r2 [num] "<<" specify r-squared threshold (default 0.9999)" << endl; - cout<<" -notsnp "<<" minor allele frequency cutoff is not used" << endl; - cout<<endl; - } - - if (option==4) { - cout<<" RELATEDNESS MATRIX CALCULATION OPTIONS" << endl; - cout<<" -gk [num] "<<" specify which type of kinship/relatedness matrix to generate (default 1)" << endl; - cout<<" options: 1: centered XX^T/p"<<endl; - cout<<" 2: standardized XX^T/p"<<endl; - cout<<" note: non-polymorphic SNPs are excluded "<<endl; - cout<<endl; - } - - if (option==5) { - cout<<" EIGEN-DECOMPOSITION OPTIONS" << endl; - cout<<" -eigen "<<" specify to perform eigen decomposition of the loaded relatedness matrix" << endl; - cout<<endl; - } - - if (option==6) { - cout<<" VARIANCE COMPONENT ESTIMATION OPTIONS" << endl; - cout<<" -vc "<<" specify to perform variance component estimation for the loaded relatedness matrix/matrices" << endl; - cout<<endl; - } - - if (option==7) { - cout<<" LINEAR MODEL OPTIONS" << endl; - cout<<" -lm [num] "<<" specify analysis options (default 1)."<<endl; - cout<<" options: 1: Wald test"<<endl; - cout<<" 2: Likelihood ratio test"<<endl; - cout<<" 3: Score test"<<endl; - cout<<" 4: 1-3"<<endl; - cout<<endl; - } - - if (option==8) { - cout<<" LINEAR MIXED MODEL OPTIONS" << endl; - cout<<" -lmm [num] "<<" specify analysis options (default 1)."<<endl; - cout<<" options: 1: Wald test"<<endl; - cout<<" 2: Likelihood ratio test"<<endl; - cout<<" 3: Score test"<<endl; - cout<<" 4: 1-3"<<endl; - cout<<" 5: Parameter estimation in the null model only"<<endl; - cout<<" -lmin [num] "<<" specify minimal value for lambda (default 1e-5)" << endl; - cout<<" -lmax [num] "<<" specify maximum value for lambda (default 1e+5)" << endl; - cout<<" -region [num] "<<" specify the number of regions used to evaluate lambda (default 10)" << endl; - cout<<endl; - } - - if (option==9) { - cout<<" MULTIVARIATE LINEAR MIXED MODEL OPTIONS" << endl; - cout<<" -pnr "<<" specify the pvalue threshold to use the Newton-Raphson's method (default 0.001)"<<endl; - cout<<" -emi "<<" specify the maximum number of iterations for the PX-EM method in the null (default 10000)"<<endl; - cout<<" -nri "<<" specify the maximum number of iterations for the Newton-Raphson's method in the null (default 100)"<<endl; - cout<<" -emp "<<" specify the precision for the PX-EM method in the null (default 0.0001)"<<endl; - cout<<" -nrp "<<" specify the precision for the Newton-Raphson's method in the null (default 0.0001)"<<endl; - cout<<" -crt "<<" specify to output corrected pvalues for these pvalues that are below the -pnr threshold"<<endl; - cout<<endl; - } - - if (option==10) { - cout<<" MULTI-LOCUS ANALYSIS OPTIONS" << endl; - cout<<" -bslmm [num] "<<" specify analysis options (default 1)."<<endl; - cout<<" options: 1: BSLMM"<<endl; - cout<<" 2: standard ridge regression/GBLUP (no mcmc)"<<endl; - cout<<" 3: probit BSLMM (requires 0/1 phenotypes)"<<endl; - - cout<<" MCMC OPTIONS" << endl; - cout<<" Prior" << endl; - cout<<" -hmin [num] "<<" specify minimum value for h (default 0)" << endl; - cout<<" -hmax [num] "<<" specify maximum value for h (default 1)" << endl; - cout<<" -rmin [num] "<<" specify minimum value for rho (default 0)" << endl; - cout<<" -rmax [num] "<<" specify maximum value for rho (default 1)" << endl; - cout<<" -pmin [num] "<<" specify minimum value for log10(pi) (default log10(1/p), where p is the number of analyzed SNPs )" << endl; - cout<<" -pmax [num] "<<" specify maximum value for log10(pi) (default log10(1) )" << endl; - cout<<" -smin [num] "<<" specify minimum value for |gamma| (default 0)" << endl; - cout<<" -smax [num] "<<" specify maximum value for |gamma| (default 300)" << endl; - - cout<<" Proposal" << endl; - cout<<" -gmean [num] "<<" specify the mean for the geometric distribution (default: 2000)" << endl; - cout<<" -hscale [num] "<<" specify the step size scale for the proposal distribution of h (value between 0 and 1, default min(10/sqrt(n),1) )" << endl; - cout<<" -rscale [num] "<<" specify the step size scale for the proposal distribution of rho (value between 0 and 1, default min(10/sqrt(n),1) )" << endl; - cout<<" -pscale [num] "<<" specify the step size scale for the proposal distribution of log10(pi) (value between 0 and 1, default min(5/sqrt(n),1) )" << endl; - - cout<<" Others" << endl; - cout<<" -w [num] "<<" specify burn-in steps (default 100,000)" << endl; - cout<<" -s [num] "<<" specify sampling steps (default 1,000,000)" << endl; - cout<<" -rpace [num] "<<" specify recording pace, record one state in every [num] steps (default 10)" << endl; - cout<<" -wpace [num] "<<" specify writing pace, write values down in every [num] recorded steps (default 1000)" << endl; - cout<<" -seed [num] "<<" specify random seed (a random seed is generated by default)" << endl; - cout<<" -mh [num] "<<" specify number of MH steps in each iteration (default 10)" << endl; - cout<<" requires: 0/1 phenotypes and -bslmm 3 option"<<endl; - cout<<endl; - } - - if (option==11) { - cout<<" PREDICTION OPTIONS" << endl; - cout<<" -predict [num] "<<" specify prediction options (default 1)."<<endl; - cout<<" options: 1: predict for individuals with missing phenotypes"<<endl; - cout<<" 2: predict for individuals with missing phenotypes, and convert the predicted values to probability scale. Use only for files fitted with -bslmm 3 option"<<endl; - cout<<endl; - } - - if (option==12) { - cout<<" NOTE"<<endl; - cout<<" 1. Only individuals with non-missing phenotoypes and covariates will be analyzed."<<endl; - cout<<" 2. Missing genotoypes will be repalced with the mean genotype of that SNP."<<endl; - cout<<" 3. For lmm analysis, memory should be large enough to hold the relatedness matrix and to perform eigen decomposition."<<endl; - cout<<" 4. For multivariate lmm analysis, use a large -pnr for each snp will increase computation time dramatically."<<endl; - cout<<" 5. For bslmm analysis, in addition to 3, memory should be large enough to hold the whole genotype matrix."<<endl; - cout<<endl; - } - - return; -} - - - -void GEMMA::Assign(int argc, char ** argv, PARAM &cPar) -{ - string str; - - for(int i = 1; i < argc; i++) { - if (strcmp(argv[i], "-bfile")==0 || strcmp(argv[i], "--bfile")==0 || strcmp(argv[i], "-b")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_bfile=str; - } - else if (strcmp(argv[i], "-silence")==0) { - cPar.mode_silence=true; - } - else if (strcmp(argv[i], "-g")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_geno=str; - } - else if (strcmp(argv[i], "-p")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_pheno=str; - } - else if (strcmp(argv[i], "-a")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_anno=str; - } - else if (strcmp(argv[i], "-k")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_kin=str; - } - else if (strcmp(argv[i], "-mk")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_mk=str; - } - else if (strcmp(argv[i], "-u")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_ku=str; - } - else if (strcmp(argv[i], "-d")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_kd=str; - } - else if (strcmp(argv[i], "-c")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_cvt=str; - } - else if (strcmp(argv[i], "-epm")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_epm=str; - } - else if (strcmp(argv[i], "-en")==0) { - while (argv[i+1] != NULL && argv[i+1][0] != '-') { - ++i; - str.clear(); - str.assign(argv[i]); - cPar.est_column.push_back(atoi(str.c_str())); - } - } - else if (strcmp(argv[i], "-ebv")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_ebv=str; - } - else if (strcmp(argv[i], "-emu")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_log=str; - } - else if (strcmp(argv[i], "-mu")==0) { - if(argv[i+1] == NULL) {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.pheno_mean=atof(str.c_str()); - } - else if (strcmp(argv[i], "-gene")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_gene=str; - } - else if (strcmp(argv[i], "-r")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_read=str; - } - else if (strcmp(argv[i], "-snps")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_snps=str; - } - else if (strcmp(argv[i], "-km")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.k_mode=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-n")==0) { - (cPar.p_column).clear(); - while (argv[i+1] != NULL && argv[i+1][0] != '-') { - ++i; - str.clear(); - str.assign(argv[i]); - (cPar.p_column).push_back(atoi(str.c_str())); - } - } - else if (strcmp(argv[i], "-pace")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.d_pace=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-outdir")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.path_out=str; - } - else if (strcmp(argv[i], "-o")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.file_out=str; - } - else if (strcmp(argv[i], "-miss")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.miss_level=atof(str.c_str()); - } - else if (strcmp(argv[i], "-maf")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - if (cPar.maf_level!=-1) {cPar.maf_level=atof(str.c_str());} - } - else if (strcmp(argv[i], "-hwe")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.hwe_level=atof(str.c_str()); - } - else if (strcmp(argv[i], "-r2")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.r2_level=atof(str.c_str()); - } - else if (strcmp(argv[i], "-notsnp")==0) { - cPar.maf_level=-1; - } - else if (strcmp(argv[i], "-gk")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=21; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=20+atoi(str.c_str()); - } - else if (strcmp(argv[i], "-eigen")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=31; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=30+atoi(str.c_str()); - } - else if (strcmp(argv[i], "-vc")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=61; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=60+atoi(str.c_str()); - } - else if (strcmp(argv[i], "-lm")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=51; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=50+atoi(str.c_str()); - } - else if (strcmp(argv[i], "-fa")==0 || strcmp(argv[i], "-lmm")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=1; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-lmin")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.l_min=atof(str.c_str()); - } - else if (strcmp(argv[i], "-lmax")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.l_max=atof(str.c_str()); - } - else if (strcmp(argv[i], "-region")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.n_region=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-pnr")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.p_nr=atof(str.c_str()); - } - else if (strcmp(argv[i], "-emi")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.em_iter=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-nri")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.nr_iter=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-emp")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.em_prec=atof(str.c_str()); - } - else if (strcmp(argv[i], "-nrp")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.nr_prec=atof(str.c_str()); - } - else if (strcmp(argv[i], "-crt")==0) { - cPar.crt=1; - } - else if (strcmp(argv[i], "-bslmm")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=11; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=10+atoi(str.c_str()); - } - else if (strcmp(argv[i], "-hmin")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.h_min=atof(str.c_str()); - } - else if (strcmp(argv[i], "-hmax")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.h_max=atof(str.c_str()); - } - else if (strcmp(argv[i], "-rmin")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.rho_min=atof(str.c_str()); - } - else if (strcmp(argv[i], "-rmax")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.rho_max=atof(str.c_str()); - } - else if (strcmp(argv[i], "-pmin")==0) { - if(argv[i+1] == NULL) {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.logp_min=atof(str.c_str())*log(10.0); - } - else if (strcmp(argv[i], "-pmax")==0) { - if(argv[i+1] == NULL) {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.logp_max=atof(str.c_str())*log(10.0); - } - else if (strcmp(argv[i], "-smin")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.s_min=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-smax")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.s_max=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-gmean")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.geo_mean=atof(str.c_str()); - } - else if (strcmp(argv[i], "-hscale")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.h_scale=atof(str.c_str()); - } - else if (strcmp(argv[i], "-rscale")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.rho_scale=atof(str.c_str()); - } - else if (strcmp(argv[i], "-pscale")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.logp_scale=atof(str.c_str())*log(10.0); - } - else if (strcmp(argv[i], "-w")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.w_step=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-s")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.s_step=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-rpace")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.r_pace=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-wpace")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.w_pace=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-seed")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.randseed=atol(str.c_str()); - } - else if (strcmp(argv[i], "-mh")==0) { - if(argv[i+1] == NULL || argv[i+1][0] == '-') {continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.n_mh=atoi(str.c_str()); - } - else if (strcmp(argv[i], "-predict")==0) { - if (cPar.a_mode!=0) {cPar.error=true; cout<<"error! only one of -gk -eigen -vc -lm -lmm -bslmm -predict options is allowed."<<endl; break;} - if(argv[i+1] == NULL || argv[i+1][0] == '-') {cPar.a_mode=41; continue;} - ++i; - str.clear(); - str.assign(argv[i]); - cPar.a_mode=40+atoi(str.c_str()); - } - else {cout<<"error! unrecognized option: "<<argv[i]<<endl; cPar.error=true; continue;} - } - - //change prediction mode to 43, if the epm file is not provided - if (cPar.a_mode==41 && cPar.file_epm.empty()) {cPar.a_mode=43;} - - return; -} - - - -void GEMMA::BatchRun (PARAM &cPar) -{ - clock_t time_begin, time_start; - time_begin=clock(); - - //Read Files - cout<<"Reading Files ... "<<endl; - cPar.ReadFiles(); - if (cPar.error==true) {cout<<"error! fail to read files. "<<endl; return;} - cPar.CheckData(); - if (cPar.error==true) {cout<<"error! fail to check data. "<<endl; return;} - //Prediction for bslmm - if (cPar.a_mode==41 || cPar.a_mode==42) { - gsl_vector *y_prdt; - - y_prdt=gsl_vector_alloc (cPar.ni_total-cPar.ni_test); - - //set to zero - gsl_vector_set_zero (y_prdt); - - PRDT cPRDT; - cPRDT.CopyFromParam(cPar); - - //add breeding value if needed - if (!cPar.file_kin.empty() && !cPar.file_ebv.empty()) { - cout<<"Adding Breeding Values ... "<<endl; - - gsl_matrix *G=gsl_matrix_alloc (cPar.ni_total, cPar.ni_total); - gsl_vector *u_hat=gsl_vector_alloc (cPar.ni_test); - - //read kinship matrix and set u_hat - vector<int> indicator_all; - size_t c_bv=0; - for (size_t i=0; i<cPar.indicator_idv.size(); i++) { - indicator_all.push_back(1); - if (cPar.indicator_bv[i]==1) {gsl_vector_set(u_hat, c_bv, cPar.vec_bv[i]); c_bv++;} - } - - ReadFile_kin (cPar.file_kin, indicator_all, cPar.mapID2num, cPar.k_mode, cPar.error, G); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - - //read u - cPRDT.AddBV(G, u_hat, y_prdt); - - gsl_matrix_free(G); - gsl_vector_free(u_hat); - } - - //add beta - if (!cPar.file_bfile.empty()) { - cPRDT.AnalyzePlink (y_prdt); - } - else { - cPRDT.AnalyzeBimbam (y_prdt); - } - - //add mu - gsl_vector_add_constant(y_prdt, cPar.pheno_mean); - - //convert y to probability if needed - if (cPar.a_mode==42) { - double d; - for (size_t i=0; i<y_prdt->size; i++) { - d=gsl_vector_get(y_prdt, i); - d=gsl_cdf_gaussian_P(d, 1.0); - gsl_vector_set(y_prdt, i, d); - } - } - - - cPRDT.CopyToParam(cPar); - - cPRDT.WriteFiles(y_prdt); - - gsl_vector_free(y_prdt); - } - - - //Prediction with kinship matrix only; for one or more phenotypes - if (cPar.a_mode==43) { - //first, use individuals with full phenotypes to obtain estimates of Vg and Ve - gsl_matrix *Y=gsl_matrix_alloc (cPar.ni_test, cPar.n_ph); - gsl_matrix *W=gsl_matrix_alloc (Y->size1, cPar.n_cvt); - gsl_matrix *G=gsl_matrix_alloc (Y->size1, Y->size1); - gsl_matrix *U=gsl_matrix_alloc (Y->size1, Y->size1); - gsl_matrix *UtW=gsl_matrix_alloc (Y->size1, W->size2); - gsl_matrix *UtY=gsl_matrix_alloc (Y->size1, Y->size2); - gsl_vector *eval=gsl_vector_alloc (Y->size1); - - gsl_matrix *Y_full=gsl_matrix_alloc (cPar.ni_cvt, cPar.n_ph); - gsl_matrix *W_full=gsl_matrix_alloc (Y_full->size1, cPar.n_cvt); - //set covariates matrix W and phenotype matrix Y - //an intercept should be included in W, - cPar.CopyCvtPhen (W, Y, 0); - cPar.CopyCvtPhen (W_full, Y_full, 1); - - gsl_matrix *Y_hat=gsl_matrix_alloc (Y_full->size1, cPar.n_ph); - gsl_matrix *G_full=gsl_matrix_alloc (Y_full->size1, Y_full->size1); - gsl_matrix *H_full=gsl_matrix_alloc (Y_full->size1*Y_hat->size2, Y_full->size1*Y_hat->size2); - - //read relatedness matrix G, and matrix G_full - ReadFile_kin (cPar.file_kin, cPar.indicator_idv, cPar.mapID2num, cPar.k_mode, cPar.error, G); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - ReadFile_kin (cPar.file_kin, cPar.indicator_cvt, cPar.mapID2num, cPar.k_mode, cPar.error, G_full); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - - //center matrix G - CenterMatrix (G); - CenterMatrix (G_full); - - //eigen-decomposition and calculate trace_G - cout<<"Start Eigen-Decomposition..."<<endl; - time_start=clock(); - cPar.trace_G=EigenDecomp (G, U, eval, 0); - cPar.trace_G=0.0; - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get (eval, i)<1e-10) {gsl_vector_set (eval, i, 0);} - cPar.trace_G+=gsl_vector_get (eval, i); - } - cPar.trace_G/=(double)eval->size; - cPar.time_eigen=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //calculate UtW and Uty - CalcUtX (U, W, UtW); - CalcUtX (U, Y, UtY); - - //calculate variance component and beta estimates - //and then obtain predicted values - if (cPar.n_ph==1) { - gsl_vector *beta=gsl_vector_alloc (W->size2); - gsl_vector *se_beta=gsl_vector_alloc (W->size2); - - double lambda, logl, vg, ve; - gsl_vector_view UtY_col=gsl_matrix_column (UtY, 0); - - //obtain estimates - CalcLambda ('R', eval, UtW, &UtY_col.vector, cPar.l_min, cPar.l_max, cPar.n_region, lambda, logl); - CalcLmmVgVeBeta (eval, UtW, &UtY_col.vector, lambda, vg, ve, beta, se_beta); - - cout<<"REMLE estimate for vg in the null model = "<<vg<<endl; - cout<<"REMLE estimate for ve in the null model = "<<ve<<endl; - cPar.vg_remle_null=vg; cPar.ve_remle_null=ve; - - //obtain Y_hat from fixed effects - gsl_vector_view Yhat_col=gsl_matrix_column (Y_hat, 0); - gsl_blas_dgemv (CblasNoTrans, 1.0, W_full, beta, 0.0, &Yhat_col.vector); - - //obtain H - gsl_matrix_set_identity (H_full); - gsl_matrix_scale (H_full, ve); - gsl_matrix_scale (G_full, vg); - gsl_matrix_add (H_full, G_full); - - //free matrices - gsl_vector_free(beta); - gsl_vector_free(se_beta); - } else { - gsl_matrix *Vg=gsl_matrix_alloc (cPar.n_ph, cPar.n_ph); - gsl_matrix *Ve=gsl_matrix_alloc (cPar.n_ph, cPar.n_ph); - gsl_matrix *B=gsl_matrix_alloc (cPar.n_ph, W->size2); - gsl_matrix *se_B=gsl_matrix_alloc (cPar.n_ph, W->size2); - - //obtain estimates - CalcMvLmmVgVeBeta (eval, UtW, UtY, cPar.em_iter, cPar.nr_iter, cPar.em_prec, cPar.nr_prec, cPar.l_min, cPar.l_max, cPar.n_region, Vg, Ve, B, se_B); - - cout<<"REMLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<Vg->size1; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(Vg, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"REMLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<Ve->size1; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(Ve, i, j)<<"\t"; - } - cout<<endl; - } - cPar.Vg_remle_null.clear(); - cPar.Ve_remle_null.clear(); - for (size_t i=0; i<Vg->size1; i++) { - for (size_t j=i; j<Vg->size2; j++) { - cPar.Vg_remle_null.push_back(gsl_matrix_get (Vg, i, j) ); - cPar.Ve_remle_null.push_back(gsl_matrix_get (Ve, i, j) ); - } - } - - //obtain Y_hat from fixed effects - gsl_blas_dgemm (CblasNoTrans, CblasTrans, 1.0, W_full, B, 0.0, Y_hat); - - //obtain H - KroneckerSym(G_full, Vg, H_full); - for (size_t i=0; i<G_full->size1; i++) { - gsl_matrix_view H_sub=gsl_matrix_submatrix (H_full, i*Ve->size1, i*Ve->size2, Ve->size1, Ve->size2); - gsl_matrix_add (&H_sub.matrix, Ve); - } - - //free matrices - gsl_matrix_free (Vg); - gsl_matrix_free (Ve); - gsl_matrix_free (B); - gsl_matrix_free (se_B); - } - - PRDT cPRDT; - - cPRDT.CopyFromParam(cPar); - - cout<<"Predicting Missing Phentypes ... "<<endl; - time_start=clock(); - cPRDT.MvnormPrdt(Y_hat, H_full, Y_full); - cPar.time_opt=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - cPRDT.WriteFiles(Y_full); - - gsl_matrix_free(Y); - gsl_matrix_free(W); - gsl_matrix_free(G); - gsl_matrix_free(U); - gsl_matrix_free(UtW); - gsl_matrix_free(UtY); - gsl_vector_free(eval); - - gsl_matrix_free(Y_full); - gsl_matrix_free(Y_hat); - gsl_matrix_free(W_full); - gsl_matrix_free(G_full); - gsl_matrix_free(H_full); - } - - - //Generate Kinship matrix - if (cPar.a_mode==21 || cPar.a_mode==22) { - cout<<"Calculating Relatedness Matrix ... "<<endl; - - gsl_matrix *G=gsl_matrix_alloc (cPar.ni_total, cPar.ni_total); - - time_start=clock(); - cPar.CalcKin (G); - cPar.time_G=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - if (cPar.error==true) {cout<<"error! fail to calculate relatedness matrix. "<<endl; return;} - - if (cPar.a_mode==21) { - cPar.WriteMatrix (G, "cXX"); - } else { - cPar.WriteMatrix (G, "sXX"); - } - - gsl_matrix_free (G); - } - - - //LM - if (cPar.a_mode==51 || cPar.a_mode==52 || cPar.a_mode==53 || cPar.a_mode==54) { //Fit LM - gsl_matrix *Y=gsl_matrix_alloc (cPar.ni_test, cPar.n_ph); - gsl_matrix *W=gsl_matrix_alloc (Y->size1, cPar.n_cvt); - - //set covariates matrix W and phenotype matrix Y - //an intercept should be included in W, - cPar.CopyCvtPhen (W, Y, 0); - - //Fit LM or mvLM - if (cPar.n_ph==1) { - LM cLm; - cLm.CopyFromParam(cPar); - - gsl_vector_view Y_col=gsl_matrix_column (Y, 0); - - if (!cPar.file_gene.empty()) { - cLm.AnalyzeGene (W, &Y_col.vector); //y is the predictor, not the phenotype - } else if (!cPar.file_bfile.empty()) { - cLm.AnalyzePlink (W, &Y_col.vector); - } else { - cLm.AnalyzeBimbam (W, &Y_col.vector); - } - - cLm.WriteFiles(); - cLm.CopyToParam(cPar); - } - /* - else { - MVLM cMvlm; - cMvlm.CopyFromParam(cPar); - - if (!cPar.file_bfile.empty()) { - cMvlm.AnalyzePlink (W, Y); - } else { - cMvlm.AnalyzeBimbam (W, Y); - } - - cMvlm.WriteFiles(); - cMvlm.CopyToParam(cPar); - } - */ - //release all matrices and vectors - gsl_matrix_free (Y); - gsl_matrix_free (W); - } - - - //VC estimation with one or multiple kinship matrices - //REML approach only - //if file_kin or file_ku/kd is provided, then a_mode is changed to 5 already, in param.cpp - //for one phenotype only; - if (cPar.a_mode==61) { - gsl_matrix *Y=gsl_matrix_alloc (cPar.ni_test, cPar.n_ph); - gsl_matrix *W=gsl_matrix_alloc (Y->size1, cPar.n_cvt); - gsl_matrix *G=gsl_matrix_alloc (Y->size1, Y->size1*cPar.n_vc ); - - //set covariates matrix W and phenotype matrix Y - //an intercept should be included in W, - cPar.CopyCvtPhen (W, Y, 0); - - //read kinship matrices - if (!(cPar.file_mk).empty()) { - ReadFile_mk (cPar.file_mk, cPar.indicator_idv, cPar.mapID2num, cPar.k_mode, cPar.error, G); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - - //center matrix G, and obtain v_traceG - double d=0; - (cPar.v_traceG).clear(); - for (size_t i=0; i<cPar.n_vc; i++) { - gsl_matrix_view G_sub=gsl_matrix_submatrix (G, 0, i*G->size1, G->size1, G->size1); - CenterMatrix (&G_sub.matrix); - d=0; - for (size_t j=0; j<G->size1; j++) { - d+=gsl_matrix_get (&G_sub.matrix, j, j); - } - d/=(double)G->size1; - (cPar.v_traceG).push_back(d); - } - } else if (!(cPar.file_kin).empty()) { - ReadFile_kin (cPar.file_kin, cPar.indicator_idv, cPar.mapID2num, cPar.k_mode, cPar.error, G); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - - //center matrix G - CenterMatrix (G); - - (cPar.v_traceG).clear(); - double d=0; - for (size_t j=0; j<G->size1; j++) { - d+=gsl_matrix_get (G, j, j); - } - d/=(double)G->size1; - (cPar.v_traceG).push_back(d); - } - /* - //eigen-decomposition and calculate trace_G - cout<<"Start Eigen-Decomposition..."<<endl; - time_start=clock(); - - if (cPar.a_mode==31) { - cPar.trace_G=EigenDecomp (G, U, eval, 1); - } else { - cPar.trace_G=EigenDecomp (G, U, eval, 0); - } - - cPar.trace_G=0.0; - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get (eval, i)<1e-10) {gsl_vector_set (eval, i, 0);} - cPar.trace_G+=gsl_vector_get (eval, i); - } - cPar.trace_G/=(double)eval->size; - - cPar.time_eigen=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } else { - ReadFile_eigenU (cPar.file_ku, cPar.error, U); - if (cPar.error==true) {cout<<"error! fail to read the U file. "<<endl; return;} - - ReadFile_eigenD (cPar.file_kd, cPar.error, eval); - if (cPar.error==true) {cout<<"error! fail to read the D file. "<<endl; return;} - - cPar.trace_G=0.0; - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get(eval, i)<1e-10) {gsl_vector_set(eval, i, 0);} - cPar.trace_G+=gsl_vector_get(eval, i); - } - cPar.trace_G/=(double)eval->size; - } - */ - //fit multiple variance components - if (cPar.n_ph==1) { - // if (cPar.n_vc==1) { - /* - //calculate UtW and Uty - CalcUtX (U, W, UtW); - CalcUtX (U, Y, UtY); - - gsl_vector_view beta=gsl_matrix_row (B, 0); - gsl_vector_view se_beta=gsl_matrix_row (se_B, 0); - gsl_vector_view UtY_col=gsl_matrix_column (UtY, 0); - - CalcLambda ('L', eval, UtW, &UtY_col.vector, cPar.l_min, cPar.l_max, cPar.n_region, cPar.l_mle_null, cPar.logl_mle_H0); - CalcLmmVgVeBeta (eval, UtW, &UtY_col.vector, cPar.l_mle_null, cPar.vg_mle_null, cPar.ve_mle_null, &beta.vector, &se_beta.vector); - - cPar.beta_mle_null.clear(); - cPar.se_beta_mle_null.clear(); - for (size_t i=0; i<B->size2; i++) { - cPar.beta_mle_null.push_back(gsl_matrix_get(B, 0, i) ); - cPar.se_beta_mle_null.push_back(gsl_matrix_get(se_B, 0, i) ); - } - - CalcLambda ('R', eval, UtW, &UtY_col.vector, cPar.l_min, cPar.l_max, cPar.n_region, cPar.l_remle_null, cPar.logl_remle_H0); - CalcLmmVgVeBeta (eval, UtW, &UtY_col.vector, cPar.l_remle_null, cPar.vg_remle_null, cPar.ve_remle_null, &beta.vector, &se_beta.vector); - cPar.beta_remle_null.clear(); - cPar.se_beta_remle_null.clear(); - for (size_t i=0; i<B->size2; i++) { - cPar.beta_remle_null.push_back(gsl_matrix_get(B, 0, i) ); - cPar.se_beta_remle_null.push_back(gsl_matrix_get(se_B, 0, i) ); - } - - CalcPve (eval, UtW, &UtY_col.vector, cPar.l_remle_null, cPar.trace_G, cPar.pve_null, cPar.pve_se_null); - cPar.PrintSummary(); - - //calculate and output residuals - if (cPar.a_mode==5) { - gsl_vector *Utu_hat=gsl_vector_alloc (Y->size1); - gsl_vector *Ute_hat=gsl_vector_alloc (Y->size1); - gsl_vector *u_hat=gsl_vector_alloc (Y->size1); - gsl_vector *e_hat=gsl_vector_alloc (Y->size1); - gsl_vector *y_hat=gsl_vector_alloc (Y->size1); - - //obtain Utu and Ute - gsl_vector_memcpy (y_hat, &UtY_col.vector); - gsl_blas_dgemv (CblasNoTrans, -1.0, UtW, &beta.vector, 1.0, y_hat); - - double d, u, e; - for (size_t i=0; i<eval->size; i++) { - d=gsl_vector_get (eval, i); - u=cPar.l_remle_null*d/(cPar.l_remle_null*d+1.0)*gsl_vector_get(y_hat, i); - e=1.0/(cPar.l_remle_null*d+1.0)*gsl_vector_get(y_hat, i); - gsl_vector_set (Utu_hat, i, u); - gsl_vector_set (Ute_hat, i, e); - } - - //obtain u and e - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Utu_hat, 0.0, u_hat); - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Ute_hat, 0.0, e_hat); - - //output residuals - cPar.WriteVector(u_hat, "residU"); - cPar.WriteVector(e_hat, "residE"); - - gsl_vector_free(u_hat); - gsl_vector_free(e_hat); - gsl_vector_free(y_hat); - } -*/ - // } else { - gsl_vector_view Y_col=gsl_matrix_column (Y, 0); - VC cVc; - cVc.CopyFromParam(cPar); - cVc.CalcVCreml (G, W, &Y_col.vector); - cVc.CopyToParam(cPar); - - //obtain pve from sigma2 - //obtain se_pve from se_sigma2 - - //} - } - - - } - - - //LMM or mvLMM or Eigen-Decomposition - if (cPar.a_mode==1 || cPar.a_mode==2 || cPar.a_mode==3 || cPar.a_mode==4 || cPar.a_mode==5 || cPar.a_mode==31) { //Fit LMM or mvLMM or eigen - gsl_matrix *Y=gsl_matrix_alloc (cPar.ni_test, cPar.n_ph); - gsl_matrix *W=gsl_matrix_alloc (Y->size1, cPar.n_cvt); - gsl_matrix *B=gsl_matrix_alloc (Y->size2, W->size2); //B is a d by c matrix - gsl_matrix *se_B=gsl_matrix_alloc (Y->size2, W->size2); - gsl_matrix *G=gsl_matrix_alloc (Y->size1, Y->size1); - gsl_matrix *U=gsl_matrix_alloc (Y->size1, Y->size1); - gsl_matrix *UtW=gsl_matrix_alloc (Y->size1, W->size2); - gsl_matrix *UtY=gsl_matrix_alloc (Y->size1, Y->size2); - gsl_vector *eval=gsl_vector_alloc (Y->size1); - - //set covariates matrix W and phenotype matrix Y - //an intercept should be included in W, - cPar.CopyCvtPhen (W, Y, 0); - - //read relatedness matrix G - if (!(cPar.file_kin).empty()) { - ReadFile_kin (cPar.file_kin, cPar.indicator_idv, cPar.mapID2num, cPar.k_mode, cPar.error, G); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - - //center matrix G - CenterMatrix (G); - - //eigen-decomposition and calculate trace_G - cout<<"Start Eigen-Decomposition..."<<endl; - time_start=clock(); - - if (cPar.a_mode==31) { - cPar.trace_G=EigenDecomp (G, U, eval, 1); - } else { - cPar.trace_G=EigenDecomp (G, U, eval, 0); - } - - cPar.trace_G=0.0; - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get (eval, i)<1e-10) {gsl_vector_set (eval, i, 0);} - cPar.trace_G+=gsl_vector_get (eval, i); - } - cPar.trace_G/=(double)eval->size; - - cPar.time_eigen=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - } else { - ReadFile_eigenU (cPar.file_ku, cPar.error, U); - if (cPar.error==true) {cout<<"error! fail to read the U file. "<<endl; return;} - - ReadFile_eigenD (cPar.file_kd, cPar.error, eval); - if (cPar.error==true) {cout<<"error! fail to read the D file. "<<endl; return;} - - cPar.trace_G=0.0; - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get(eval, i)<1e-10) {gsl_vector_set(eval, i, 0);} - cPar.trace_G+=gsl_vector_get(eval, i); - } - cPar.trace_G/=(double)eval->size; - } - - if (cPar.a_mode==31) { - cPar.WriteMatrix(U, "eigenU"); - cPar.WriteVector(eval, "eigenD"); - } else { - //calculate UtW and Uty - CalcUtX (U, W, UtW); - CalcUtX (U, Y, UtY); - - //calculate REMLE/MLE estimate and pve for univariate model - if (cPar.n_ph==1) { - gsl_vector_view beta=gsl_matrix_row (B, 0); - gsl_vector_view se_beta=gsl_matrix_row (se_B, 0); - gsl_vector_view UtY_col=gsl_matrix_column (UtY, 0); - - CalcLambda ('L', eval, UtW, &UtY_col.vector, cPar.l_min, cPar.l_max, cPar.n_region, cPar.l_mle_null, cPar.logl_mle_H0); - CalcLmmVgVeBeta (eval, UtW, &UtY_col.vector, cPar.l_mle_null, cPar.vg_mle_null, cPar.ve_mle_null, &beta.vector, &se_beta.vector); - - cPar.beta_mle_null.clear(); - cPar.se_beta_mle_null.clear(); - for (size_t i=0; i<B->size2; i++) { - cPar.beta_mle_null.push_back(gsl_matrix_get(B, 0, i) ); - cPar.se_beta_mle_null.push_back(gsl_matrix_get(se_B, 0, i) ); - } - - CalcLambda ('R', eval, UtW, &UtY_col.vector, cPar.l_min, cPar.l_max, cPar.n_region, cPar.l_remle_null, cPar.logl_remle_H0); - CalcLmmVgVeBeta (eval, UtW, &UtY_col.vector, cPar.l_remle_null, cPar.vg_remle_null, cPar.ve_remle_null, &beta.vector, &se_beta.vector); - cPar.beta_remle_null.clear(); - cPar.se_beta_remle_null.clear(); - for (size_t i=0; i<B->size2; i++) { - cPar.beta_remle_null.push_back(gsl_matrix_get(B, 0, i) ); - cPar.se_beta_remle_null.push_back(gsl_matrix_get(se_B, 0, i) ); - } - - CalcPve (eval, UtW, &UtY_col.vector, cPar.l_remle_null, cPar.trace_G, cPar.pve_null, cPar.pve_se_null); - cPar.PrintSummary(); - - //calculate and output residuals - if (cPar.a_mode==5) { - gsl_vector *Utu_hat=gsl_vector_alloc (Y->size1); - gsl_vector *Ute_hat=gsl_vector_alloc (Y->size1); - gsl_vector *u_hat=gsl_vector_alloc (Y->size1); - gsl_vector *e_hat=gsl_vector_alloc (Y->size1); - gsl_vector *y_hat=gsl_vector_alloc (Y->size1); - - //obtain Utu and Ute - gsl_vector_memcpy (y_hat, &UtY_col.vector); - gsl_blas_dgemv (CblasNoTrans, -1.0, UtW, &beta.vector, 1.0, y_hat); - - double d, u, e; - for (size_t i=0; i<eval->size; i++) { - d=gsl_vector_get (eval, i); - u=cPar.l_remle_null*d/(cPar.l_remle_null*d+1.0)*gsl_vector_get(y_hat, i); - e=1.0/(cPar.l_remle_null*d+1.0)*gsl_vector_get(y_hat, i); - gsl_vector_set (Utu_hat, i, u); - gsl_vector_set (Ute_hat, i, e); - } - - //obtain u and e - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Utu_hat, 0.0, u_hat); - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Ute_hat, 0.0, e_hat); - - //output residuals - cPar.WriteVector(u_hat, "residU"); - cPar.WriteVector(e_hat, "residE"); - - gsl_vector_free(u_hat); - gsl_vector_free(e_hat); - gsl_vector_free(y_hat); - } - } - - //Fit LMM or mvLMM - if (cPar.a_mode==1 || cPar.a_mode==2 || cPar.a_mode==3 || cPar.a_mode==4) { - if (cPar.n_ph==1) { - LMM cLmm; - cLmm.CopyFromParam(cPar); - - gsl_vector_view Y_col=gsl_matrix_column (Y, 0); - gsl_vector_view UtY_col=gsl_matrix_column (UtY, 0); - - if (!cPar.file_gene.empty()) { - cLmm.AnalyzeGene (U, eval, UtW, &UtY_col.vector, W, &Y_col.vector); //y is the predictor, not the phenotype - } else if (!cPar.file_bfile.empty()) { - cLmm.AnalyzePlink (U, eval, UtW, &UtY_col.vector, W, &Y_col.vector); - } else { - cLmm.AnalyzeBimbam (U, eval, UtW, &UtY_col.vector, W, &Y_col.vector); - } - - cLmm.WriteFiles(); - cLmm.CopyToParam(cPar); - } else { - MVLMM cMvlmm; - cMvlmm.CopyFromParam(cPar); - - if (!cPar.file_bfile.empty()) { - cMvlmm.AnalyzePlink (U, eval, UtW, UtY); - } else { - cMvlmm.AnalyzeBimbam (U, eval, UtW, UtY); - } - - cMvlmm.WriteFiles(); - cMvlmm.CopyToParam(cPar); - } - } - } - - - //release all matrices and vectors - gsl_matrix_free (Y); - gsl_matrix_free (W); - gsl_matrix_free(B); - gsl_matrix_free(se_B); - gsl_matrix_free (G); - gsl_matrix_free (U); - gsl_matrix_free (UtW); - gsl_matrix_free (UtY); - gsl_vector_free (eval); - } - - - //BSLMM - if (cPar.a_mode==11 || cPar.a_mode==12 || cPar.a_mode==13) { - gsl_vector *y=gsl_vector_alloc (cPar.ni_test); - gsl_matrix *W=gsl_matrix_alloc (y->size, cPar.n_cvt); - gsl_matrix *G=gsl_matrix_alloc (y->size, y->size); - gsl_matrix *UtX=gsl_matrix_alloc (y->size, cPar.ns_test); - - //set covariates matrix W and phenotype vector y - //an intercept should be included in W, - cPar.CopyCvtPhen (W, y, 0); - - //center y, even for case/control data - cPar.pheno_mean=CenterVector(y); - - //run bslmm if rho==1 - if (cPar.rho_min==1 && cPar.rho_max==1) { - //read genotypes X (not UtX) - cPar.ReadGenotypes (UtX, G, false); - - //perform BSLMM analysis - BSLMM cBslmm; - cBslmm.CopyFromParam(cPar); - time_start=clock(); - cBslmm.MCMC(UtX, y); - cPar.time_opt=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - cBslmm.CopyToParam(cPar); - //else, if rho!=1 - } else { - gsl_matrix *U=gsl_matrix_alloc (y->size, y->size); - gsl_vector *eval=gsl_vector_alloc (y->size); - gsl_matrix *UtW=gsl_matrix_alloc (y->size, W->size2); - gsl_vector *Uty=gsl_vector_alloc (y->size); - - - //read relatedness matrix G - if (!(cPar.file_kin).empty()) { - cPar.ReadGenotypes (UtX, G, false); - - //read relatedness matrix G - ReadFile_kin (cPar.file_kin, cPar.indicator_idv, cPar.mapID2num, cPar.k_mode, cPar.error, G); - if (cPar.error==true) {cout<<"error! fail to read kinship/relatedness file. "<<endl; return;} - - //center matrix G - CenterMatrix (G); - } else { - cPar.ReadGenotypes (UtX, G, true); - } - - //eigen-decomposition and calculate trace_G - cout<<"Start Eigen-Decomposition..."<<endl; - time_start=clock(); - cPar.trace_G=EigenDecomp (G, U, eval, 0); - cPar.trace_G=0.0; - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get (eval, i)<1e-10) {gsl_vector_set (eval, i, 0);} - cPar.trace_G+=gsl_vector_get (eval, i); - } - cPar.trace_G/=(double)eval->size; - cPar.time_eigen=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //calculate UtW and Uty - CalcUtX (U, W, UtW); - CalcUtX (U, y, Uty); - - //calculate REMLE/MLE estimate and pve - CalcLambda ('L', eval, UtW, Uty, cPar.l_min, cPar.l_max, cPar.n_region, cPar.l_mle_null, cPar.logl_mle_H0); - CalcLambda ('R', eval, UtW, Uty, cPar.l_min, cPar.l_max, cPar.n_region, cPar.l_remle_null, cPar.logl_remle_H0); - CalcPve (eval, UtW, Uty, cPar.l_remle_null, cPar.trace_G, cPar.pve_null, cPar.pve_se_null); - - cPar.PrintSummary(); - - //Creat and calcualte UtX, use a large memory - cout<<"Calculating UtX..."<<endl; - time_start=clock(); - CalcUtX (U, UtX); - cPar.time_UtX=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //perform BSLMM analysis - BSLMM cBslmm; - cBslmm.CopyFromParam(cPar); - time_start=clock(); - if (cPar.a_mode==12) { //ridge regression - cBslmm.RidgeR(U, UtX, Uty, eval, cPar.l_remle_null); - } else { //Run MCMC - cBslmm.MCMC(U, UtX, Uty, eval, y); - } - cPar.time_opt=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - cBslmm.CopyToParam(cPar); - - //release all matrices and vectors - gsl_matrix_free (G); - gsl_matrix_free (U); - gsl_matrix_free (UtW); - gsl_vector_free (eval); - gsl_vector_free (Uty); - - } - gsl_matrix_free (W); - gsl_vector_free (y); - gsl_matrix_free (UtX); - } - - - - cPar.time_total=(clock()-time_begin)/(double(CLOCKS_PER_SEC)*60.0); - - return; -} - - - - -void GEMMA::WriteLog (int argc, char ** argv, PARAM &cPar) -{ - string file_str; - file_str=cPar.path_out+"/"+cPar.file_out; - file_str+=".log.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing log file: "<<file_str.c_str()<<endl; return;} - - outfile<<"##"<<endl; - outfile<<"## GEMMA Version = "<<version<<endl; - - outfile<<"##"<<endl; - outfile<<"## Command Line Input = "; - for(int i = 1; i < argc; i++) { - outfile<<argv[i]<<" "; - } - outfile<<endl; - - outfile<<"##"<<endl; - time_t rawtime; - time(&rawtime); - tm *ptm = localtime (&rawtime); - - outfile<<"## Date = "<<asctime(ptm)<<endl; - //ptm->tm_year<<":"<<ptm->tm_month<<":"<<ptm->tm_day":"<<ptm->tm_hour<<":"<<ptm->tm_min<<endl; - - outfile<<"##"<<endl; - outfile<<"## Summary Statistics:"<<endl; - outfile<<"## number of total individuals = "<<cPar.ni_total<<endl; - if (cPar.a_mode==43) { - outfile<<"## number of analyzed individuals = "<<cPar.ni_cvt<<endl; - outfile<<"## number of individuals with full phenotypes = "<<cPar.ni_test<<endl; - } else { - outfile<<"## number of analyzed individuals = "<<cPar.ni_test<<endl; - } - outfile<<"## number of covariates = "<<cPar.n_cvt<<endl; - outfile<<"## number of phenotypes = "<<cPar.n_ph<<endl; - if (cPar.a_mode==43) { - outfile<<"## number of observed data = "<<cPar.np_obs<<endl; - outfile<<"## number of missing data = "<<cPar.np_miss<<endl; - } - if (cPar.a_mode==61) { - outfile<<"## number of variance components = "<<cPar.n_vc<<endl; - } - - if (!(cPar.file_gene).empty()) { - outfile<<"## number of total genes = "<<cPar.ng_total<<endl; - outfile<<"## number of analyzed genes = "<<cPar.ng_test<<endl; - } else if (cPar.file_epm.empty()) { - outfile<<"## number of total SNPs = "<<cPar.ns_total<<endl; - outfile<<"## number of analyzed SNPs = "<<cPar.ns_test<<endl; - } else { - outfile<<"## number of analyzed SNPs = "<<cPar.ns_test<<endl; - } - - if (cPar.a_mode==13) { - outfile<<"## number of cases = "<<cPar.ni_case<<endl; - outfile<<"## number of controls = "<<cPar.ni_control<<endl; - } - - - if (cPar.a_mode==61) { - // outfile<<"## REMLE log-likelihood in the null model = "<<cPar.logl_remle_H0<<endl; - if (cPar.n_ph==1) { - outfile<<"## pve estimate in the null model = "; - for (size_t i=0; i<cPar.v_pve.size(); i++) { - outfile<<" "<<cPar.v_pve[i]; - } - outfile<<endl; - - outfile<<"## se(pve) in the null model = "; - for (size_t i=0; i<cPar.v_se_pve.size(); i++) { - outfile<<" "<<cPar.v_se_pve[i]; - } - outfile<<endl; - - outfile<<"## sigma2 estimate in the null model = "; - for (size_t i=0; i<cPar.v_sigma2.size(); i++) { - outfile<<" "<<cPar.v_sigma2[i]; - } - outfile<<endl; - - outfile<<"## se(sigma2) in the null model = "; - for (size_t i=0; i<cPar.v_se_sigma2.size(); i++) { - outfile<<" "<<cPar.v_se_sigma2[i]; - } - outfile<<endl; - /* - outfile<<"## beta estimate in the null model = "; - for (size_t i=0; i<cPar.beta_remle_null.size(); i++) { - outfile<<" "<<cPar.beta_remle_null[i]; - } - outfile<<endl; - outfile<<"## se(beta) = "; - for (size_t i=0; i<cPar.se_beta_remle_null.size(); i++) { - outfile<<" "<<cPar.se_beta_remle_null[i]; - } - outfile<<endl; - */ - } - } - - if (cPar.a_mode==1 || cPar.a_mode==2 || cPar.a_mode==3 || cPar.a_mode==4 || cPar.a_mode==5 || cPar.a_mode==11 || cPar.a_mode==12 || cPar.a_mode==13) { - outfile<<"## REMLE log-likelihood in the null model = "<<cPar.logl_remle_H0<<endl; - outfile<<"## MLE log-likelihood in the null model = "<<cPar.logl_mle_H0<<endl; - if (cPar.n_ph==1) { - //outfile<<"## lambda REMLE estimate in the null (linear mixed) model = "<<cPar.l_remle_null<<endl; - //outfile<<"## lambda MLE estimate in the null (linear mixed) model = "<<cPar.l_mle_null<<endl; - outfile<<"## pve estimate in the null model = "<<cPar.pve_null<<endl; - outfile<<"## se(pve) in the null model = "<<cPar.pve_se_null<<endl; - outfile<<"## vg estimate in the null model = "<<cPar.vg_remle_null<<endl; - outfile<<"## ve estimate in the null model = "<<cPar.ve_remle_null<<endl; - outfile<<"## beta estimate in the null model = "; - for (size_t i=0; i<cPar.beta_remle_null.size(); i++) { - outfile<<" "<<cPar.beta_remle_null[i]; - } - outfile<<endl; - outfile<<"## se(beta) = "; - for (size_t i=0; i<cPar.se_beta_remle_null.size(); i++) { - outfile<<" "<<cPar.se_beta_remle_null[i]; - } - outfile<<endl; - - } else { - size_t c; - outfile<<"## REMLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<cPar.Vg_remle_null[c]<<"\t"; - } - outfile<<endl; - } - outfile<<"## se(Vg): "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<sqrt(cPar.VVg_remle_null[c])<<"\t"; - } - outfile<<endl; - } - outfile<<"## REMLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<cPar.Ve_remle_null[c]<<"\t"; - } - outfile<<endl; - } - outfile<<"## se(Ve): "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<sqrt(cPar.VVe_remle_null[c])<<"\t"; - } - outfile<<endl; - } - - outfile<<"## MLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<cPar.n_ph; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<cPar.Vg_mle_null[c]<<"\t"; - } - outfile<<endl; - } - outfile<<"## se(Vg): "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<sqrt(cPar.VVg_mle_null[c])<<"\t"; - } - outfile<<endl; - } - outfile<<"## MLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<cPar.n_ph; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<cPar.Ve_mle_null[c]<<"\t"; - } - outfile<<endl; - } - outfile<<"## se(Ve): "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<sqrt(cPar.VVe_mle_null[c])<<"\t"; - } - outfile<<endl; - } - outfile<<"## estimate for B (d by c) in the null model (columns correspond to the covariates provided in the file): "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<cPar.n_cvt; j++) { - c=i*cPar.n_cvt+j; - outfile<<cPar.beta_remle_null[c]<<"\t"; - } - outfile<<endl; - } - outfile<<"## se(B): "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<cPar.n_cvt; j++) { - c=i*cPar.n_cvt+j; - outfile<<cPar.se_beta_remle_null[c]<<"\t"; - } - outfile<<endl; - } - } - } - - /* - if (cPar.a_mode==1 || cPar.a_mode==2 || cPar.a_mode==3 || cPar.a_mode==4 || cPar.a_mode==11 || cPar.a_mode==12 || cPar.a_mode==13) { - if (cPar.n_ph==1) { - outfile<<"## REMLE vg estimate in the null model = "<<cPar.vg_remle_null<<endl; - outfile<<"## REMLE ve estimate in the null model = "<<cPar.ve_remle_null<<endl; - } else { - size_t c; - outfile<<"## REMLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<cPar.Vg_remle_null[c]<<"\t"; - } - outfile<<endl; - } - outfile<<"## REMLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<cPar.n_ph; i++) { - for (size_t j=0; j<=i; j++) { - c=(2*cPar.n_ph-min(i,j)+1)*min(i,j)/2+max(i,j)-min(i,j); - outfile<<cPar.Ve_remle_null[c]<<"\t"; - } - outfile<<endl; - } - } - } - */ - - - if (cPar.a_mode==11 || cPar.a_mode==12 || cPar.a_mode==13) { - outfile<<"## estimated mean = "<<cPar.pheno_mean<<endl; - } - - if (cPar.a_mode==11 || cPar.a_mode==13) { - outfile<<"##"<<endl; - outfile<<"## MCMC related:"<<endl; - outfile<<"## initial value of h = "<<cPar.cHyp_initial.h<<endl; - outfile<<"## initial value of rho = "<<cPar.cHyp_initial.rho<<endl; - outfile<<"## initial value of pi = "<<exp(cPar.cHyp_initial.logp)<<endl; - outfile<<"## initial value of |gamma| = "<<cPar.cHyp_initial.n_gamma<<endl; - outfile<<"## random seed = "<<cPar.randseed<<endl; - outfile<<"## acceptance ratio = "<<(double)cPar.n_accept/(double)((cPar.w_step+cPar.s_step)*cPar.n_mh)<<endl; - } - - outfile<<"##"<<endl; - outfile<<"## Computation Time:"<<endl; - outfile<<"## total computation time = "<<cPar.time_total<<" min "<<endl; - outfile<<"## computation time break down: "<<endl; - if (cPar.a_mode==21 || cPar.a_mode==22 || cPar.a_mode==11 || cPar.a_mode==13) { - outfile<<"## time on calculating relatedness matrix = "<<cPar.time_G<<" min "<<endl; - } - if (cPar.a_mode==31) { - outfile<<"## time on eigen-decomposition = "<<cPar.time_eigen<<" min "<<endl; - } - if (cPar.a_mode==1 || cPar.a_mode==2 || cPar.a_mode==3 || cPar.a_mode==4 || cPar.a_mode==5 || cPar.a_mode==11 || cPar.a_mode==12 || cPar.a_mode==13) { - outfile<<"## time on eigen-decomposition = "<<cPar.time_eigen<<" min "<<endl; - outfile<<"## time on calculating UtX = "<<cPar.time_UtX<<" min "<<endl; - } - if ((cPar.a_mode>=1 && cPar.a_mode<=4) || (cPar.a_mode>=51 && cPar.a_mode<=54) ) { - outfile<<"## time on optimization = "<<cPar.time_opt<<" min "<<endl; - } - if (cPar.a_mode==11 || cPar.a_mode==13) { - outfile<<"## time on proposal = "<<cPar.time_Proposal<<" min "<<endl; - outfile<<"## time on mcmc = "<<cPar.time_opt<<" min "<<endl; - outfile<<"## time on Omega = "<<cPar.time_Omega<<" min "<<endl; - } - if (cPar.a_mode==41 || cPar.a_mode==42) { - outfile<<"## time on eigen-decomposition = "<<cPar.time_eigen<<" min "<<endl; - } - if (cPar.a_mode==43) { - outfile<<"## time on eigen-decomposition = "<<cPar.time_eigen<<" min "<<endl; - outfile<<"## time on predicting phenotypes = "<<cPar.time_opt<<" min "<<endl; - } - outfile<<"##"<<endl; - - outfile.close(); - outfile.clear(); - return; -} - - diff --git a/gemma.h b/gemma.h deleted file mode 100644 index acb1309..0000000 --- a/gemma.h +++ /dev/null @@ -1,52 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __GEMMA_H__ -#define __GEMMA_H__ - -#ifdef FORCE_FLOAT -#include "param_float.h" -#else -#include "param.h" -#endif - -using namespace std; - -class GEMMA { - -public: - //parameters - string version; - string date; - string year; - - //constructor - GEMMA(void); - - //functions - void PrintHeader (void); - void PrintHelp (size_t option); - void PrintLicense (void); - void Assign (int argc, char **argv, PARAM &cPar); - void BatchRun (PARAM &cPar); - void WriteLog (int argc, char **argv, PARAM &cPar); -}; - - -#endif - diff --git a/gzstream.cpp b/gzstream.cpp deleted file mode 100644 index bbb4ba8..0000000 --- a/gzstream.cpp +++ /dev/null @@ -1,165 +0,0 @@ -// ============================================================================ -// gzstream, C++ iostream classes wrapping the zlib compression library. -// Copyright (C) 2001 Deepak Bandyopadhyay, Lutz Kettner -// -// This library is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 2.1 of the License, or (at your option) any later version. -// -// This library is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU -// Lesser General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License along with this library; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA -// ============================================================================ -// -// File : gzstream.C -// Revision : $Revision: 1.7 $ -// Revision_date : $Date: 2003/01/08 14:41:27 $ -// Author(s) : Deepak Bandyopadhyay, Lutz Kettner -// -// Standard streambuf implementation following Nicolai Josuttis, "The -// Standard C++ Library". -// ============================================================================ - -#include "gzstream.h" -#include <iostream> -#include <string.h> // for memcpy - -#ifdef GZSTREAM_NAMESPACE -namespace GZSTREAM_NAMESPACE { -#endif - -// ---------------------------------------------------------------------------- -// Internal classes to implement gzstream. See header file for user classes. -// ---------------------------------------------------------------------------- - -// -------------------------------------- -// class gzstreambuf: -// -------------------------------------- - -gzstreambuf* gzstreambuf::open( const char* name, int open_mode) { - if ( is_open()) - return (gzstreambuf*)0; - mode = open_mode; - // no append nor read/write mode - if ((mode & std::ios::ate) || (mode & std::ios::app) - || ((mode & std::ios::in) && (mode & std::ios::out))) - return (gzstreambuf*)0; - char fmode[10]; - char* fmodeptr = fmode; - if ( mode & std::ios::in) - *fmodeptr++ = 'r'; - else if ( mode & std::ios::out) - *fmodeptr++ = 'w'; - *fmodeptr++ = 'b'; - *fmodeptr = '\0'; - file = gzopen( name, fmode); - if (file == 0) - return (gzstreambuf*)0; - opened = 1; - return this; -} - -gzstreambuf * gzstreambuf::close() { - if ( is_open()) { - sync(); - opened = 0; - if ( gzclose( file) == Z_OK) - return this; - } - return (gzstreambuf*)0; -} - -int gzstreambuf::underflow() { // used for input buffer only - if ( gptr() && ( gptr() < egptr())) - return * reinterpret_cast<unsigned char *>( gptr()); - - if ( ! (mode & std::ios::in) || ! opened) - return EOF; - // Josuttis' implementation of inbuf - int n_putback = gptr() - eback(); - if ( n_putback > 4) - n_putback = 4; - memcpy( buffer + (4 - n_putback), gptr() - n_putback, n_putback); - - int num = gzread( file, buffer+4, bufferSize-4); - if (num <= 0) // ERROR or EOF - return EOF; - - // reset buffer pointers - setg( buffer + (4 - n_putback), // beginning of putback area - buffer + 4, // read position - buffer + 4 + num); // end of buffer - - // return next character - return * reinterpret_cast<unsigned char *>( gptr()); -} - -int gzstreambuf::flush_buffer() { - // Separate the writing of the buffer from overflow() and - // sync() operation. - int w = pptr() - pbase(); - if ( gzwrite( file, pbase(), w) != w) - return EOF; - pbump( -w); - return w; -} - -int gzstreambuf::overflow( int c) { // used for output buffer only - if ( ! ( mode & std::ios::out) || ! opened) - return EOF; - if (c != EOF) { - *pptr() = c; - pbump(1); - } - if ( flush_buffer() == EOF) - return EOF; - return c; -} - -int gzstreambuf::sync() { - // Changed to use flush_buffer() instead of overflow( EOF) - // which caused improper behavior with std::endl and flush(), - // bug reported by Vincent Ricard. - if ( pptr() && pptr() > pbase()) { - if ( flush_buffer() == EOF) - return -1; - } - return 0; -} - -// -------------------------------------- -// class gzstreambase: -// -------------------------------------- - -gzstreambase::gzstreambase( const char* name, int mode) { - init( &buf); - open( name, mode); -} - -gzstreambase::~gzstreambase() { - buf.close(); -} - -void gzstreambase::open( const char* name, int open_mode) { - if ( ! buf.open( name, open_mode)) - clear( rdstate() | std::ios::badbit); -} - -void gzstreambase::close() { - if ( buf.is_open()) - if ( ! buf.close()) - clear( rdstate() | std::ios::badbit); -} - -#ifdef GZSTREAM_NAMESPACE -} // namespace GZSTREAM_NAMESPACE -#endif - -// ============================================================================ -// EOF // diff --git a/gzstream.h b/gzstream.h deleted file mode 100644 index 861653f..0000000 --- a/gzstream.h +++ /dev/null @@ -1,121 +0,0 @@ -// ============================================================================ -// gzstream, C++ iostream classes wrapping the zlib compression library. -// Copyright (C) 2001 Deepak Bandyopadhyay, Lutz Kettner -// -// This library is free software; you can redistribute it and/or -// modify it under the terms of the GNU Lesser General Public -// License as published by the Free Software Foundation; either -// version 2.1 of the License, or (at your option) any later version. -// -// This library is distributed in the hope that it will be useful, -// but WITHOUT ANY WARRANTY; without even the implied warranty of -// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU -// Lesser General Public License for more details. -// -// You should have received a copy of the GNU Lesser General Public -// License along with this library; if not, write to the Free Software -// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA -// ============================================================================ -// -// File : gzstream.h -// Revision : $Revision: 1.5 $ -// Revision_date : $Date: 2002/04/26 23:30:15 $ -// Author(s) : Deepak Bandyopadhyay, Lutz Kettner -// -// Standard streambuf implementation following Nicolai Josuttis, "The -// Standard C++ Library". -// ============================================================================ - -#ifndef GZSTREAM_H -#define GZSTREAM_H 1 - -// standard C++ with new header file names and std:: namespace -#include <iostream> -#include <fstream> -#include <zlib.h> - -#ifdef GZSTREAM_NAMESPACE -namespace GZSTREAM_NAMESPACE { -#endif - -// ---------------------------------------------------------------------------- -// Internal classes to implement gzstream. See below for user classes. -// ---------------------------------------------------------------------------- - -class gzstreambuf : public std::streambuf { -private: - static const int bufferSize = 47+256; // size of data buff - // totals 512 bytes under g++ for igzstream at the end. - - gzFile file; // file handle for compressed file - char buffer[bufferSize]; // data buffer - char opened; // open/close state of stream - int mode; // I/O mode - - int flush_buffer(); -public: - gzstreambuf() : opened(0) { - setp( buffer, buffer + (bufferSize-1)); - setg( buffer + 4, // beginning of putback area - buffer + 4, // read position - buffer + 4); // end position - // ASSERT: both input & output capabilities will not be used together - } - int is_open() { return opened; } - gzstreambuf* open( const char* name, int open_mode); - gzstreambuf* close(); - ~gzstreambuf() { close(); } - - virtual int overflow( int c = EOF); - virtual int underflow(); - virtual int sync(); -}; - -class gzstreambase : virtual public std::ios { -protected: - gzstreambuf buf; -public: - gzstreambase() { init(&buf); } - gzstreambase( const char* name, int open_mode); - ~gzstreambase(); - void open( const char* name, int open_mode); - void close(); - gzstreambuf* rdbuf() { return &buf; } -}; - -// ---------------------------------------------------------------------------- -// User classes. Use igzstream and ogzstream analogously to ifstream and -// ofstream respectively. They read and write files based on the gz* -// function interface of the zlib. Files are compatible with gzip compression. -// ---------------------------------------------------------------------------- - -class igzstream : public gzstreambase, public std::istream { -public: - igzstream() : std::istream( &buf) {} - igzstream( const char* name, int open_mode = std::ios::in) - : gzstreambase( name, open_mode), std::istream( &buf) {} - gzstreambuf* rdbuf() { return gzstreambase::rdbuf(); } - void open( const char* name, int open_mode = std::ios::in) { - gzstreambase::open( name, open_mode); - } -}; - -class ogzstream : public gzstreambase, public std::ostream { -public: - ogzstream() : std::ostream( &buf) {} - ogzstream( const char* name, int mode = std::ios::out) - : gzstreambase( name, mode), std::ostream( &buf) {} - gzstreambuf* rdbuf() { return gzstreambase::rdbuf(); } - void open( const char* name, int open_mode = std::ios::out) { - gzstreambase::open( name, open_mode); - } -}; - -#ifdef GZSTREAM_NAMESPACE -} // namespace GZSTREAM_NAMESPACE -#endif - -#endif // GZSTREAM_H -// ============================================================================ -// EOF // - diff --git a/io.cpp b/io.cpp deleted file mode 100644 index c22f668..0000000 --- a/io.cpp +++ /dev/null @@ -1,1396 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#include <iostream> -#include <fstream> -#include <sstream> -#include <string> -#include <iomanip> -#include <bitset> -#include <vector> -#include <map> -#include <set> -#include <cstring> -#include <cmath> -#include <stdio.h> -#include <stdlib.h> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" -#include "gsl/gsl_cdf.h" - -#include "lapack.h" -#include "gzstream.h" -#include "mathfunc.h" - -#ifdef FORCE_FLOAT -#include "io_float.h" -#else -#include "io.h" -#endif - - -using namespace std; - - - -//Print process bar -void ProgressBar (string str, double p, double total) -{ - double progress = (100.0 * p / total); - int barsize = (int) (progress / 2.0); - char bar[51]; - - cout<<str; - for (int i = 0; i <50; i++) { - if (i<barsize) {bar[i] = '=';} - else {bar[i]=' ';} - cout<<bar[i]; - } - cout<<setprecision(2)<<fixed<<progress<<"%\r"<<flush; - - return; -} - - -//Print process bar (with acceptance ratio) -void ProgressBar (string str, double p, double total, double ratio) -{ - double progress = (100.0 * p / total); - int barsize = (int) (progress / 2.0); - char bar[51]; - - cout<<str; - for (int i = 0; i <50; i++) { - if (i<barsize) {bar[i] = '=';} - else {bar[i]=' ';} - cout<<bar[i]; - } - cout<<setprecision(2)<<fixed<<progress<<"% "<<ratio<<"\r"<<flush; - - - return; -} - -// in case files are ended with "\r" or "\r\n" -std::istream& safeGetline(std::istream& is, std::string& t) -{ - t.clear(); - - // The characters in the stream are read one-by-one using a std::streambuf. - // That is faster than reading them one-by-one using the std::istream. - // Code that uses streambuf this way must be guarded by a sentry object. - // The sentry object performs various tasks, - // such as thread synchronization and updating the stream state. - - std::istream::sentry se(is, true); - std::streambuf* sb = is.rdbuf(); - - for(;;) { - int c = sb->sbumpc(); - switch (c) { - case '\n': - return is; - case '\r': - if(sb->sgetc() == '\n') - sb->sbumpc(); - return is; - case EOF: - // Also handle the case when the last line has no line ending - if(t.empty()) - is.setstate(std::ios::eofbit); - return is; - default: - t += (char)c; - } - } -} - -//Read snp file -bool ReadFile_snps (const string &file_snps, set<string> &setSnps) -{ - setSnps.clear(); - - ifstream infile (file_snps.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open snps file: "<<file_snps<<endl; return false;} - - string line; - char *ch_ptr; - - while (getline(infile, line)) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - setSnps.insert(ch_ptr); - } - - infile.close(); - infile.clear(); - - return true; -} - - -//Read log file -bool ReadFile_log (const string &file_log, double &pheno_mean) -{ - ifstream infile (file_log.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open log file: "<<file_log<<endl; return false;} - - string line; - char *ch_ptr; - size_t flag=0; - - while (getline(infile, line)) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - if (ch_ptr!=NULL && strcmp(ch_ptr, "estimated")==0) { - ch_ptr=strtok (NULL, " , \t"); - if (ch_ptr!=NULL && strcmp(ch_ptr, "mean")==0) { - ch_ptr=strtok (NULL, " , \t"); - if (ch_ptr!=NULL && strcmp(ch_ptr, "=")==0) { - ch_ptr=strtok (NULL, " , \t"); - pheno_mean=atof(ch_ptr); - flag=1; - } - } - } - - if (flag==1) {break;} - } - - infile.close(); - infile.clear(); - - return true; -} - - -//Read bimbam annotation file -bool ReadFile_anno (const string &file_anno, map<string, string> &mapRS2chr, map<string, long int> &mapRS2bp, map<string, double> &mapRS2cM) -{ - mapRS2chr.clear(); - mapRS2bp.clear(); - - ifstream infile (file_anno.c_str(), ifstream::in); - if (!infile) {cout<<"error opening annotation file: "<<file_anno<<endl; return false;} - - string line; - char *ch_ptr; - - string rs; - long int b_pos; - string chr; - double cM; - - while (!safeGetline(infile, line).eof()) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - rs=ch_ptr; - ch_ptr=strtok (NULL, " , \t"); - if (strcmp(ch_ptr, "NA")==0) {b_pos=-9;} else {b_pos=atol(ch_ptr);} - ch_ptr=strtok (NULL, " , \t"); - if (ch_ptr==NULL || strcmp(ch_ptr, "NA")==0) {chr="-9";} else {chr=ch_ptr;} - ch_ptr=strtok (NULL, " , \t"); - if (ch_ptr==NULL || strcmp(ch_ptr, "NA")==0) {cM=-9;} else {cM=atof(ch_ptr);} - - mapRS2chr[rs]=chr; - mapRS2bp[rs]=b_pos; - mapRS2cM[rs]=cM; - } - - infile.close(); - infile.clear(); - - return true; -} - -//read one column of phenotype -bool ReadFile_column (const string &file_pheno, vector<int> &indicator_idv, vector<double> &pheno, const int &p_column) -{ - indicator_idv.clear(); - pheno.clear(); - - igzstream infile (file_pheno.c_str(), igzstream::in); -// ifstream infile (file_pheno.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open phenotype file: "<<file_pheno<<endl; return false;} - - string line; - char *ch_ptr; - - string id; - double p; - while (!safeGetline(infile, line).eof()) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - for (int i=0; i<(p_column-1); ++i) { - ch_ptr=strtok (NULL, " , \t"); - } - if (strcmp(ch_ptr, "NA")==0) {indicator_idv.push_back(0); pheno.push_back(-9);} //pheno is different from pimass2 - else {p=atof(ch_ptr); indicator_idv.push_back(1); pheno.push_back(p);} - } - - infile.close(); - infile.clear(); - - return true; -} - - - -//Read bimbam phenotype file, p_column=1, 2 ... -bool ReadFile_pheno (const string &file_pheno, vector<vector<int> > &indicator_pheno, vector<vector<double> > &pheno, const vector<size_t> &p_column) -{ - indicator_pheno.clear(); - pheno.clear(); - - igzstream infile (file_pheno.c_str(), igzstream::in); -// ifstream infile (file_pheno.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open phenotype file: "<<file_pheno<<endl; return false;} - - string line; - char *ch_ptr; - - string id; - double p; - - vector<double> pheno_row; - vector<int> ind_pheno_row; - - size_t p_max=*max_element(p_column.begin(), p_column.end() ); - map<size_t, size_t> mapP2c; - for (size_t i=0; i<p_column.size(); i++) { - mapP2c[p_column[i]]=i; - pheno_row.push_back(-9); - ind_pheno_row.push_back(0); - } - - while (!safeGetline(infile, line).eof()) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - - size_t i=0; - while (i<p_max ) { - if (mapP2c.count(i+1)!=0) { - if (strcmp(ch_ptr, "NA")==0) {ind_pheno_row[mapP2c[i+1]]=0; pheno_row[mapP2c[i+1]]=-9;} - else {p=atof(ch_ptr); ind_pheno_row[mapP2c[i+1]]=1; pheno_row[mapP2c[i+1]]=p;} - } - i++; - ch_ptr=strtok (NULL, " , \t"); - } - - indicator_pheno.push_back(ind_pheno_row); - pheno.push_back(pheno_row); - } - - infile.close(); - infile.clear(); - - return true; -} - - -bool ReadFile_cvt (const string &file_cvt, vector<int> &indicator_cvt, vector<vector<double> > &cvt, size_t &n_cvt) -{ - indicator_cvt.clear(); - - ifstream infile (file_cvt.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open covariates file: "<<file_cvt<<endl; return false;} - - string line; - char *ch_ptr; - double d; - - int flag_na=0; - - while (!safeGetline(infile, line).eof()) { - vector<double> v_d; flag_na=0; - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - while (ch_ptr!=NULL) { - if (strcmp(ch_ptr, "NA")==0) {flag_na=1; d=-9;} - else {d=atof(ch_ptr);} - - v_d.push_back(d); - ch_ptr=strtok (NULL, " , \t"); - } - if (flag_na==0) {indicator_cvt.push_back(1);} else {indicator_cvt.push_back(0);} - cvt.push_back(v_d); - } - - if (indicator_cvt.empty()) {n_cvt=0;} - else { - flag_na=0; - for (vector<int>::size_type i=0; i<indicator_cvt.size(); ++i) { - if (indicator_cvt[i]==0) {continue;} - - if (flag_na==0) {flag_na=1; n_cvt=cvt[i].size();} - if (flag_na!=0 && n_cvt!=cvt[i].size()) {cout<<"error! number of covariates in row "<<i<<" do not match other rows."<<endl; return false;} - } - } - - infile.close(); - infile.clear(); - - return true; -} - - - -//Read .bim file -bool ReadFile_bim (const string &file_bim, vector<SNPINFO> &snpInfo) -{ - snpInfo.clear(); - - ifstream infile (file_bim.c_str(), ifstream::in); - if (!infile) {cout<<"error opening .bim file: "<<file_bim<<endl; return false;} - - string line; - char *ch_ptr; - - string rs; - long int b_pos; - string chr; - double cM; - string major; - string minor; - - while (getline(infile, line)) { - ch_ptr=strtok ((char *)line.c_str(), " \t"); - chr=ch_ptr; - ch_ptr=strtok (NULL, " \t"); - rs=ch_ptr; - ch_ptr=strtok (NULL, " \t"); - cM=atof(ch_ptr); - ch_ptr=strtok (NULL, " \t"); - b_pos=atol(ch_ptr); - ch_ptr=strtok (NULL, " \t"); - minor=ch_ptr; - ch_ptr=strtok (NULL, " \t"); - major=ch_ptr; - - SNPINFO sInfo={chr, rs, cM, b_pos, minor, major, -9, -9, -9}; - snpInfo.push_back(sInfo); - } - - infile.close(); - infile.clear(); - return true; -} - - -//Read .fam file -bool ReadFile_fam (const string &file_fam, vector<vector<int> > &indicator_pheno, vector<vector<double> > &pheno, map<string, int> &mapID2num, const vector<size_t> &p_column) -{ - indicator_pheno.clear(); - pheno.clear(); - mapID2num.clear(); - - igzstream infile (file_fam.c_str(), igzstream::in); - //ifstream infile (file_fam.c_str(), ifstream::in); - if (!infile) {cout<<"error opening .fam file: "<<file_fam<<endl; return false;} - - string line; - char *ch_ptr; - - string id; - int c=0; - double p; - - vector<double> pheno_row; - vector<int> ind_pheno_row; - - size_t p_max=*max_element(p_column.begin(), p_column.end() ); - map<size_t, size_t> mapP2c; - for (size_t i=0; i<p_column.size(); i++) { - mapP2c[p_column[i]]=i; - pheno_row.push_back(-9); - ind_pheno_row.push_back(0); - } - - while (!safeGetline(infile, line).eof()) { - ch_ptr=strtok ((char *)line.c_str(), " \t"); - ch_ptr=strtok (NULL, " \t"); - id=ch_ptr; - ch_ptr=strtok (NULL, " \t"); - ch_ptr=strtok (NULL, " \t"); - ch_ptr=strtok (NULL, " \t"); - ch_ptr=strtok (NULL, " \t"); - - size_t i=0; - while (i<p_max ) { - if (mapP2c.count(i+1)!=0 ) { - if (strcmp(ch_ptr, "NA")==0) { - ind_pheno_row[mapP2c[i+1]]=0; pheno_row[mapP2c[i+1]]=-9; - } else { - p=atof(ch_ptr); - - if (p==-9) {ind_pheno_row[mapP2c[i+1]]=0; pheno_row[mapP2c[i+1]]=-9;} - else {ind_pheno_row[mapP2c[i+1]]=1; pheno_row[mapP2c[i+1]]=p;} - } - } - i++; - ch_ptr=strtok (NULL, " , \t"); - } - - indicator_pheno.push_back(ind_pheno_row); - pheno.push_back(pheno_row); - - mapID2num[id]=c; c++; - } - - infile.close(); - infile.clear(); - return true; -} - - - - - - -//Read bimbam mean genotype file, the first time, to obtain #SNPs for analysis (ns_test) and total #SNP (ns_total) -bool ReadFile_geno (const string &file_geno, const set<string> &setSnps, const gsl_matrix *W, vector<int> &indicator_idv, vector<int> &indicator_snp, const double &maf_level, const double &miss_level, const double &hwe_level, const double &r2_level, map<string, string> &mapRS2chr, map<string, long int> &mapRS2bp, map<string, double> &mapRS2cM, vector<SNPINFO> &snpInfo, size_t &ns_test) -{ - indicator_snp.clear(); - snpInfo.clear(); - - igzstream infile (file_geno.c_str(), igzstream::in); -// ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return false;} - - gsl_vector *genotype=gsl_vector_alloc (W->size1); - gsl_vector *genotype_miss=gsl_vector_alloc (W->size1); - gsl_matrix *WtW=gsl_matrix_alloc (W->size2, W->size2); - gsl_matrix *WtWi=gsl_matrix_alloc (W->size2, W->size2); - gsl_vector *Wtx=gsl_vector_alloc (W->size2); - gsl_vector *WtWiWtx=gsl_vector_alloc (W->size2); - gsl_permutation * pmt=gsl_permutation_alloc (W->size2); - - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, W, W, 0.0, WtW); - int sig; - LUDecomp (WtW, pmt, &sig); - LUInvert (WtW, pmt, WtWi); - - double v_x, v_w; - int c_idv=0; - - string line; - char *ch_ptr; - - string rs; - long int b_pos; - string chr; - string major; - string minor; - double cM; - - double maf, geno, geno_old; - size_t n_miss; - size_t n_0, n_1, n_2; - int flag_poly; - - int ni_total=indicator_idv.size(); - int ni_test=0; - for (int i=0; i<ni_total; ++i) { - ni_test+=indicator_idv[i]; - } - ns_test=0; - - while (!safeGetline(infile, line).eof()) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - rs=ch_ptr; - ch_ptr=strtok (NULL, " , \t"); - minor=ch_ptr; - ch_ptr=strtok (NULL, " , \t"); - major=ch_ptr; - - if (setSnps.size()!=0 && setSnps.count(rs)==0) { - SNPINFO sInfo={"-9", rs, -9, -9, minor, major, -9, -9, -9}; - snpInfo.push_back(sInfo); - indicator_snp.push_back(0); - continue; - } - - if (mapRS2bp.count(rs)==0) {chr="-9"; b_pos=-9;cM=-9;} - else {b_pos=mapRS2bp[rs]; chr=mapRS2chr[rs]; cM=mapRS2cM[rs];} - - maf=0; n_miss=0; flag_poly=0; geno_old=-9; - n_0=0; n_1=0; n_2=0; - c_idv=0; gsl_vector_set_zero (genotype_miss); - for (int i=0; i<ni_total; ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==0) {continue;} - - if (strcmp(ch_ptr, "NA")==0) {gsl_vector_set (genotype_miss, c_idv, 1); n_miss++; c_idv++; continue;} - - geno=atof(ch_ptr); - if (geno>=0 && geno<=0.5) {n_0++;} - if (geno>0.5 && geno<1.5) {n_1++;} - if (geno>=1.5 && geno<=2.0) {n_2++;} - - gsl_vector_set (genotype, c_idv, geno); - -// if (geno<0) {n_miss++; continue;} - - if (flag_poly==0) {geno_old=geno; flag_poly=2;} - if (flag_poly==2 && geno!=geno_old) {flag_poly=1;} - - maf+=geno; - - c_idv++; - } - maf/=2.0*(double)(ni_test-n_miss); - - SNPINFO sInfo={chr, rs, cM, b_pos, minor, major, n_miss, (double)n_miss/(double)ni_test, maf}; - snpInfo.push_back(sInfo); - - if ( (double)n_miss/(double)ni_test > miss_level) {indicator_snp.push_back(0); continue;} - - if ( (maf<maf_level || maf> (1.0-maf_level)) && maf_level!=-1 ) {indicator_snp.push_back(0); continue;} - - if (flag_poly!=1) {indicator_snp.push_back(0); continue;} - - if (hwe_level!=0) { - if (CalcHWE(n_0, n_2, n_1)<hwe_level) {indicator_snp.push_back(0); continue;} - } - - //filter SNP if it is correlated with W - for (size_t i=0; i<genotype->size; ++i) { - if (gsl_vector_get (genotype_miss, i)==1) {geno=maf*2.0; gsl_vector_set (genotype, i, geno);} - } - - gsl_blas_dgemv (CblasTrans, 1.0, W, genotype, 0.0, Wtx); - gsl_blas_dgemv (CblasNoTrans, 1.0, WtWi, Wtx, 0.0, WtWiWtx); - gsl_blas_ddot (genotype, genotype, &v_x); - gsl_blas_ddot (Wtx, WtWiWtx, &v_w); - - if (v_w/v_x >= r2_level) {indicator_snp.push_back(0); continue;} - - indicator_snp.push_back(1); - ns_test++; - } - - gsl_vector_free (genotype); - gsl_vector_free (genotype_miss); - gsl_matrix_free (WtW); - gsl_matrix_free (WtWi); - gsl_vector_free (Wtx); - gsl_vector_free (WtWiWtx); - gsl_permutation_free (pmt); - - infile.close(); - infile.clear(); - - return true; -} - - - - - - -//Read bed file, the first time -bool ReadFile_bed (const string &file_bed, const set<string> &setSnps, const gsl_matrix *W, vector<int> &indicator_idv, vector<int> &indicator_snp, vector<SNPINFO> &snpInfo, const double &maf_level, const double &miss_level, const double &hwe_level, const double &r2_level, size_t &ns_test) -{ - indicator_snp.clear(); - size_t ns_total=snpInfo.size(); - - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return false;} - - gsl_vector *genotype=gsl_vector_alloc (W->size1); - gsl_vector *genotype_miss=gsl_vector_alloc (W->size1); - gsl_matrix *WtW=gsl_matrix_alloc (W->size2, W->size2); - gsl_matrix *WtWi=gsl_matrix_alloc (W->size2, W->size2); - gsl_vector *Wtx=gsl_vector_alloc (W->size2); - gsl_vector *WtWiWtx=gsl_vector_alloc (W->size2); - gsl_permutation * pmt=gsl_permutation_alloc (W->size2); - - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, W, W, 0.0, WtW); - int sig; - LUDecomp (WtW, pmt, &sig); - LUInvert (WtW, pmt, WtWi); - - double v_x, v_w, geno; - size_t c_idv=0; - - char ch[1]; - bitset<8> b; - - size_t ni_total=indicator_idv.size(); - size_t ni_test=0; - for (size_t i=0; i<ni_total; ++i) { - ni_test+=indicator_idv[i]; - } - ns_test=0; - - //calculate n_bit and c, the number of bit for each snp - size_t n_bit; - if (ni_total%4==0) {n_bit=ni_total/4;} - else {n_bit=ni_total/4+1;} - - //ignore the first three majic numbers - for (int i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - double maf; - size_t n_miss; - size_t n_0, n_1, n_2, c; - - //start reading snps and doing association test - for (size_t t=0; t<ns_total; ++t) { - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - if (setSnps.size()!=0 && setSnps.count(snpInfo[t].rs_number)==0) { - snpInfo[t].n_miss=-9; - snpInfo[t].missingness=-9; - snpInfo[t].maf=-9; - indicator_snp.push_back(0); - continue; - } - - //read genotypes - c=0; maf=0.0; n_miss=0; n_0=0; n_1=0; n_2=0; - c_idv=0; gsl_vector_set_zero (genotype_miss); - for (size_t i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && c==ni_total) {break;} - if (indicator_idv[c]==0) {c++; continue;} - c++; - - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(genotype, c_idv, 2.0); maf+=2.0; n_2++;} - else {gsl_vector_set(genotype, c_idv, 1.0); maf+=1.0; n_1++;} - } - else { - if (b[2*j+1]==1) {gsl_vector_set(genotype, c_idv, 0.0); maf+=0.0; n_0++;} - else {gsl_vector_set(genotype_miss, c_idv, 1); n_miss++; } - } - c_idv++; - } - } - maf/=2.0*(double)(ni_test-n_miss); - - snpInfo[t].n_miss=n_miss; - snpInfo[t].missingness=(double)n_miss/(double)ni_test; - snpInfo[t].maf=maf; - - if ( (double)n_miss/(double)ni_test > miss_level) {indicator_snp.push_back(0); continue;} - - if ( (maf<maf_level || maf> (1.0-maf_level)) && maf_level!=-1 ) {indicator_snp.push_back(0); continue;} - - if ( (n_0+n_1)==0 || (n_1+n_2)==0 || (n_2+n_0)==0) {indicator_snp.push_back(0); continue;} - - if (hwe_level!=1) { - if (CalcHWE(n_0, n_2, n_1)<hwe_level) {indicator_snp.push_back(0); continue;} - } - - - //filter SNP if it is correlated with W - for (size_t i=0; i<genotype->size; ++i) { - if (gsl_vector_get (genotype_miss, i)==1) {geno=maf*2.0; gsl_vector_set (genotype, i, geno);} - } - - gsl_blas_dgemv (CblasTrans, 1.0, W, genotype, 0.0, Wtx); - gsl_blas_dgemv (CblasNoTrans, 1.0, WtWi, Wtx, 0.0, WtWiWtx); - gsl_blas_ddot (genotype, genotype, &v_x); - gsl_blas_ddot (Wtx, WtWiWtx, &v_w); - - if (v_w/v_x > r2_level) {indicator_snp.push_back(0); continue;} - - indicator_snp.push_back(1); - ns_test++; - } - - gsl_vector_free (genotype); - gsl_vector_free (genotype_miss); - gsl_matrix_free (WtW); - gsl_matrix_free (WtWi); - gsl_vector_free (Wtx); - gsl_vector_free (WtWiWtx); - gsl_permutation_free (pmt); - - infile.close(); - infile.clear(); - - return true; -} - - - -void ReadFile_kin (const string &file_kin, vector<int> &indicator_idv, map<string, int> &mapID2num, const size_t k_mode, bool &error, gsl_matrix *G) -{ - igzstream infile (file_kin.c_str(), igzstream::in); -// ifstream infile (file_kin.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open kinship file: "<<file_kin<<endl; error=true; return;} - - size_t ni_total=indicator_idv.size(); - - gsl_matrix_set_zero (G); - - string line; - char *ch_ptr; - double d; - - if (k_mode==1) { - size_t i_test=0, i_total=0, j_test=0, j_total=0; - while (getline(infile, line)) { - if (i_total==ni_total) {cout<<"error! number of rows in the kinship file is larger than the number of phentypes."<<endl; error=true;} - - if (indicator_idv[i_total]==0) {i_total++; continue;} - - j_total=0; j_test=0; - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - while (ch_ptr!=NULL) { - if (j_total==ni_total) {cout<<"error! number of columns in the kinship file is larger than the number of phentypes for row = "<<i_total<<endl; error=true;} - - d=atof(ch_ptr); - if (indicator_idv[j_total]==1) {gsl_matrix_set (G, i_test, j_test, d); j_test++;} - j_total++; - - ch_ptr=strtok (NULL, " , \t"); - } - if (j_total!=ni_total) {cout<<"error! number of columns in the kinship file do not match the number of phentypes for row = "<<i_total<<endl; error=true;} - i_total++; i_test++; - } - if (i_total!=ni_total) {cout<<"error! number of rows in the kinship file do not match the number of phentypes."<<endl; error=true;} - } - else { - map<size_t, size_t> mapID2ID; - size_t c=0; - for (size_t i=0; i<indicator_idv.size(); i++) { - if (indicator_idv[i]==1) {mapID2ID[i]=c; c++;} - } - - string id1, id2; - double Cov_d; - size_t n_id1, n_id2; - - while (getline(infile, line)) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - id1=ch_ptr; - ch_ptr=strtok (NULL, " , \t"); - id2=ch_ptr; - ch_ptr=strtok (NULL, " , \t"); - d=atof(ch_ptr); - if (mapID2num.count(id1)==0 || mapID2num.count(id2)==0) {continue;} - if (indicator_idv[mapID2num[id1]]==0 || indicator_idv[mapID2num[id2]]==0) {continue;} - - n_id1=mapID2ID[mapID2num[id1]]; - n_id2=mapID2ID[mapID2num[id2]]; - - Cov_d=gsl_matrix_get(G, n_id1, n_id2); - if (Cov_d!=0 && Cov_d!=d) {cout<<"error! redundant and unequal terms in the kinship file, for id1 = "<<id1<<" and id2 = "<<id2<<endl;} - else { - gsl_matrix_set(G, n_id1, n_id2, d); - gsl_matrix_set(G, n_id2, n_id1, d); - } - } - } - - infile.close(); - infile.clear(); - - return; -} - - -void ReadFile_mk (const string &file_mk, vector<int> &indicator_idv, map<string, int> &mapID2num, const size_t k_mode, bool &error, gsl_matrix *G) -{ - igzstream infile (file_mk.c_str(), igzstream::in); - if (!infile) {cout<<"error! fail to open file: "<<file_mk<<endl; error=true; return;} - - string file_kin, line; - - size_t i=0; - while (getline(infile, line)) { - file_kin=line.c_str(); - gsl_matrix_view G_sub=gsl_matrix_submatrix(G, 0, i*G->size1, G->size1, G->size1); - ReadFile_kin (file_kin, indicator_idv, mapID2num, k_mode, error, &G_sub.matrix); - i++; - } - - infile.close(); - infile.clear(); - return; -} - - -void ReadFile_eigenU (const string &file_ku, bool &error, gsl_matrix *U) -{ - igzstream infile (file_ku.c_str(), igzstream::in); -// ifstream infile (file_ku.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open the U file: "<<file_ku<<endl; error=true; return;} - - size_t n_row=U->size1, n_col=U->size2, i_row=0, i_col=0; - - gsl_matrix_set_zero (U); - - string line; - char *ch_ptr; - double d; - - while (getline(infile, line)) { - if (i_row==n_row) {cout<<"error! number of rows in the U file is larger than expected."<<endl; error=true;} - - i_col=0; - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - while (ch_ptr!=NULL) { - if (i_col==n_col) {cout<<"error! number of columns in the U file is larger than expected, for row = "<<i_row<<endl; error=true;} - - d=atof(ch_ptr); - gsl_matrix_set (U, i_row, i_col, d); - i_col++; - - ch_ptr=strtok (NULL, " , \t"); - } - - i_row++; - } - - infile.close(); - infile.clear(); - - return; -} - - - - -void ReadFile_eigenD (const string &file_kd, bool &error, gsl_vector *eval) -{ - igzstream infile (file_kd.c_str(), igzstream::in); -// ifstream infile (file_kd.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open the D file: "<<file_kd<<endl; error=true; return;} - - size_t n_row=eval->size, i_row=0; - - gsl_vector_set_zero (eval); - - string line; - char *ch_ptr; - double d; - - while (getline(infile, line)) { - if (i_row==n_row) {cout<<"error! number of rows in the D file is larger than expected."<<endl; error=true;} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - d=atof(ch_ptr); - - ch_ptr=strtok (NULL, " , \t"); - if (ch_ptr!=NULL) {cout<<"error! number of columns in the D file is larger than expected, for row = "<<i_row<<endl; error=true;} - - gsl_vector_set (eval, i_row, d); - - i_row++; - } - - infile.close(); - infile.clear(); - - return; -} - - - -//read bimbam mean genotype file and calculate kinship matrix -bool BimbamKin (const string &file_geno, vector<int> &indicator_snp, const int k_mode, const int display_pace, gsl_matrix *matrix_kin) -{ - igzstream infile (file_geno.c_str(), igzstream::in); - //ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return false;} - - string line; - char *ch_ptr; - - size_t n_miss; - double d, geno_mean, geno_var; - - size_t ni_total=matrix_kin->size1; - gsl_vector *geno=gsl_vector_alloc (ni_total); - gsl_vector *geno_miss=gsl_vector_alloc (ni_total); - - size_t ns_test=0; - for (size_t t=0; t<indicator_snp.size(); ++t) { - !safeGetline(infile, line).eof(); - if (t%display_pace==0 || t==(indicator_snp.size()-1)) {ProgressBar ("Reading SNPs ", t, indicator_snp.size()-1);} - if (indicator_snp[t]==0) {continue;} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - ch_ptr=strtok (NULL, " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - geno_mean=0.0; n_miss=0; geno_var=0.0; - gsl_vector_set_all(geno_miss, 0); - for (size_t i=0; i<ni_total; ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (strcmp(ch_ptr, "NA")==0) {gsl_vector_set(geno_miss, i, 0); n_miss++;} - else { - d=atof(ch_ptr); - gsl_vector_set (geno, i, d); - gsl_vector_set (geno_miss, i, 1); - geno_mean+=d; - geno_var+=d*d; - } - } - - geno_mean/=(double)(ni_total-n_miss); - geno_var+=geno_mean*geno_mean*(double)n_miss; - geno_var/=(double)ni_total; - geno_var-=geno_mean*geno_mean; -// geno_var=geno_mean*(1-geno_mean*0.5); - - for (size_t i=0; i<ni_total; ++i) { - if (gsl_vector_get (geno_miss, i)==0) {gsl_vector_set(geno, i, geno_mean);} - } - - gsl_vector_add_constant (geno, -1.0*geno_mean); - - if (geno_var!=0) { - if (k_mode==1) {gsl_blas_dsyr (CblasUpper, 1.0, geno, matrix_kin);} - else if (k_mode==2) {gsl_blas_dsyr (CblasUpper, 1.0/geno_var, geno, matrix_kin);} - else {cout<<"Unknown kinship mode."<<endl;} - } - - ns_test++; - } - cout<<endl; - - gsl_matrix_scale (matrix_kin, 1.0/(double)ns_test); - - for (size_t i=0; i<ni_total; ++i) { - for (size_t j=0; j<i; ++j) { - d=gsl_matrix_get (matrix_kin, j, i); - gsl_matrix_set (matrix_kin, i, j, d); - } - } - - gsl_vector_free (geno); - gsl_vector_free (geno_miss); - - infile.close(); - infile.clear(); - - return true; -} - - - - - - - -bool PlinkKin (const string &file_bed, vector<int> &indicator_snp, const int k_mode, const int display_pace, gsl_matrix *matrix_kin) -{ - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return false;} - - char ch[1]; - bitset<8> b; - - size_t n_miss, ci_total; - double d, geno_mean, geno_var; - - size_t ni_total=matrix_kin->size1; - gsl_vector *geno=gsl_vector_alloc (ni_total); - - size_t ns_test=0; - int n_bit; - - //calculate n_bit and c, the number of bit for each snp - if (ni_total%4==0) {n_bit=ni_total/4;} - else {n_bit=ni_total/4+1; } - - //print the first three majic numbers - for (int i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - for (size_t t=0; t<indicator_snp.size(); ++t) { - if (t%display_pace==0 || t==(indicator_snp.size()-1)) {ProgressBar ("Reading SNPs ", t, indicator_snp.size()-1);} - if (indicator_snp[t]==0) {continue;} - - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - //read genotypes - geno_mean=0.0; n_miss=0; ci_total=0; geno_var=0.0; - for (int i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && ci_total==ni_total) {break;} - - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(geno, ci_total, 2.0); geno_mean+=2.0; geno_var+=4.0; } - else {gsl_vector_set(geno, ci_total, 1.0); geno_mean+=1.0; geno_var+=1.0;} - } - else { - if (b[2*j+1]==1) {gsl_vector_set(geno, ci_total, 0.0); } - else {gsl_vector_set(geno, ci_total, -9.0); n_miss++; } - } - - ci_total++; - } - } - - geno_mean/=(double)(ni_total-n_miss); - geno_var+=geno_mean*geno_mean*(double)n_miss; - geno_var/=(double)ni_total; - geno_var-=geno_mean*geno_mean; -// geno_var=geno_mean*(1-geno_mean*0.5); - - for (size_t i=0; i<ni_total; ++i) { - d=gsl_vector_get(geno,i); - if (d==-9.0) {gsl_vector_set(geno, i, geno_mean);} - } - - gsl_vector_add_constant (geno, -1.0*geno_mean); - - if (geno_var!=0) { - if (k_mode==1) {gsl_blas_dsyr (CblasUpper, 1.0, geno, matrix_kin);} - else if (k_mode==2) {gsl_blas_dsyr (CblasUpper, 1.0/geno_var, geno, matrix_kin);} - else {cout<<"Unknown kinship mode."<<endl;} - } - - ns_test++; - } - cout<<endl; - - gsl_matrix_scale (matrix_kin, 1.0/(double)ns_test); - - for (size_t i=0; i<ni_total; ++i) { - for (size_t j=0; j<i; ++j) { - d=gsl_matrix_get (matrix_kin, j, i); - gsl_matrix_set (matrix_kin, i, j, d); - } - } - - gsl_vector_free (geno); - - infile.close(); - infile.clear(); - - return true; -} - - - - - -//Read bimbam mean genotype file, the second time, recode "mean" genotype and calculate K -bool ReadFile_geno (const string &file_geno, vector<int> &indicator_idv, vector<int> &indicator_snp, gsl_matrix *UtX, gsl_matrix *K, const bool calc_K) -{ - igzstream infile (file_geno.c_str(), igzstream::in); -// ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return false;} - - string line; - char *ch_ptr; - - if (calc_K==true) {gsl_matrix_set_zero (K);} - - gsl_vector *genotype=gsl_vector_alloc (UtX->size1); - gsl_vector *genotype_miss=gsl_vector_alloc (UtX->size1); - double geno, geno_mean; - size_t n_miss; - - int ni_total=(int)indicator_idv.size(); - int ns_total=(int)indicator_snp.size(); - int ni_test=UtX->size1; - int ns_test=UtX->size2; - - int c_idv=0, c_snp=0; - - for (int i=0; i<ns_total; ++i) { - !safeGetline(infile, line).eof(); - if (indicator_snp[i]==0) {continue;} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - ch_ptr=strtok (NULL, " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - c_idv=0; geno_mean=0; n_miss=0; - gsl_vector_set_zero (genotype_miss); - for (int j=0; j<ni_total; ++j) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[j]==0) {continue;} - - if (strcmp(ch_ptr, "NA")==0) {gsl_vector_set (genotype_miss, c_idv, 1); n_miss++;} - else { - geno=atof(ch_ptr); - gsl_vector_set (genotype, c_idv, geno); - geno_mean+=geno; - } - c_idv++; - } - - geno_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<genotype->size; ++i) { - if (gsl_vector_get (genotype_miss, i)==1) {geno=0;} - else {geno=gsl_vector_get (genotype, i); geno-=geno_mean;} - - gsl_vector_set (genotype, i, geno); - gsl_matrix_set (UtX, i, c_snp, geno); - } - - if (calc_K==true) {gsl_blas_dsyr (CblasUpper, 1.0, genotype, K);} - - c_snp++; - } - - if (calc_K==true) { - gsl_matrix_scale (K, 1.0/(double)ns_test); - - for (size_t i=0; i<genotype->size; ++i) { - for (size_t j=0; j<i; ++j) { - geno=gsl_matrix_get (K, j, i); - gsl_matrix_set (K, i, j, geno); - } - } - } - - gsl_vector_free (genotype); - gsl_vector_free (genotype_miss); - - infile.clear(); - infile.close(); - - return true; -} - - - - - - - -//Read bimbam mean genotype file, the second time, recode "mean" genotype and calculate K -bool ReadFile_bed (const string &file_bed, vector<int> &indicator_idv, vector<int> &indicator_snp, gsl_matrix *UtX, gsl_matrix *K, const bool calc_K) -{ - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return false;} - - char ch[1]; - bitset<8> b; - - int ni_total=(int)indicator_idv.size(); - int ns_total=(int)indicator_snp.size(); - int ni_test=UtX->size1; - int ns_test=UtX->size2; - int n_bit; - - if (ni_total%4==0) {n_bit=ni_total/4;} - else {n_bit=ni_total/4+1;} - - //print the first three majic numbers - for (int i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - if (calc_K==true) {gsl_matrix_set_zero (K);} - - gsl_vector *genotype=gsl_vector_alloc (UtX->size1); - - double geno, geno_mean; - size_t n_miss; - int c_idv=0, c_snp=0, c=0; - - //start reading snps and doing association test - for (int t=0; t<ns_total; ++t) { - if (indicator_snp[t]==0) {continue;} - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - //read genotypes - c_idv=0; geno_mean=0.0; n_miss=0; c=0; - for (int i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && c==ni_total) {break;} - if (indicator_idv[c]==0) {c++; continue;} - c++; - - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(genotype, c_idv, 2.0); geno_mean+=2.0;} - else {gsl_vector_set(genotype, c_idv, 1.0); geno_mean+=1.0;} - } - else { - if (b[2*j+1]==1) {gsl_vector_set(genotype, c_idv, 0.0); geno_mean+=0.0;} - else {gsl_vector_set(genotype, c_idv, -9.0); n_miss++;} - } - c_idv++; - } - } - - geno_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<genotype->size; ++i) { - geno=gsl_vector_get (genotype, i); - if (geno==-9) {geno=0;} - else {geno-=geno_mean;} - - gsl_vector_set (genotype, i, geno); - gsl_matrix_set (UtX, i, c_snp, geno); - } - - if (calc_K==true) {gsl_blas_dsyr (CblasUpper, 1.0, genotype, K);} - - c_snp++; - } - - if (calc_K==true) { - gsl_matrix_scale (K, 1.0/(double)ns_test); - - for (size_t i=0; i<genotype->size; ++i) { - for (size_t j=0; j<i; ++j) { - geno=gsl_matrix_get (K, j, i); - gsl_matrix_set (K, i, j, geno); - } - } - } - - gsl_vector_free (genotype); - infile.clear(); - infile.close(); - - return true; -} - - - - - -bool ReadFile_est (const string &file_est, const vector<size_t> &est_column, map<string, double> &mapRS2est) -{ - mapRS2est.clear(); - - ifstream infile (file_est.c_str(), ifstream::in); - if (!infile) {cout<<"error opening estimated parameter file: "<<file_est<<endl; return false;} - - string line; - char *ch_ptr; - - string rs; - double alpha, beta, gamma, d; - - //header - getline(infile, line); - - size_t n=*max_element(est_column.begin(), est_column.end()); - - while (getline(infile, line)) { - ch_ptr=strtok ((char *)line.c_str(), " \t"); - - alpha=0.0; beta=0.0; gamma=1.0; - for (size_t i=0; i<n+1; ++i) { - if (i==est_column[0]-1) {rs=ch_ptr;} - if (i==est_column[1]-1) {alpha=atof(ch_ptr);} - if (i==est_column[2]-1) {beta=atof(ch_ptr);} - if (i==est_column[3]-1) {gamma=atof(ch_ptr);} - if (i<n) {ch_ptr=strtok (NULL, " \t");} - } - - d=alpha+beta*gamma; - - if (mapRS2est.count(rs)==0) { - mapRS2est[rs]=d; - } - else { - cout<<"the same SNP occurs more than once in estimated parameter file: "<<rs<<endl; return false; - } - } - - infile.clear(); - infile.close(); - return true; -} - - - -bool CountFileLines (const string &file_input, size_t &n_lines) -{ - igzstream infile (file_input.c_str(), igzstream::in); - //ifstream infile (file_input.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open file: "<<file_input<<endl; return false;} - - n_lines=count(istreambuf_iterator<char>(infile), istreambuf_iterator<char>(), '\n'); - infile.seekg (0, ios::beg); - - return true; -} - - - -//Read gene expression file -bool ReadFile_gene (const string &file_gene, vector<double> &vec_read, vector<SNPINFO> &snpInfo, size_t &ng_total) -{ - vec_read.clear(); - ng_total=0; - - ifstream infile (file_gene.c_str(), ifstream::in); - if (!infile) {cout<<"error! fail to open gene expression file: "<<file_gene<<endl; return false;} - - string line; - char *ch_ptr; - string rs; - - size_t n_idv=0, t=0; - - //header - getline(infile, line); - - while (getline(infile, line)) { - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - rs=ch_ptr; - - ch_ptr=strtok (NULL, " , \t"); - - t=0; - while (ch_ptr!=NULL) { - if (ng_total==0) { - vec_read.push_back(0); - t++; - n_idv++; - } else { - vec_read[t]+=atof(ch_ptr); - t++; - } - - ch_ptr=strtok (NULL, " , \t"); - } - - if (t!=n_idv) {cout<<"error! number of columns doesn't match in row: "<<ng_total<<endl; return false;} - - SNPINFO sInfo={"-9", rs, -9, -9, "-9", "-9", -9, -9, -9}; - snpInfo.push_back(sInfo); - - ng_total++; - } - - infile.close(); - infile.clear(); - - return true; -} - - diff --git a/io.h b/io.h deleted file mode 100644 index 13e3e47..0000000 --- a/io.h +++ /dev/null @@ -1,79 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __IO_H__ -#define __IO_H__ - - -#include <vector> -#include <map> -#include <algorithm> -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - -#ifdef FORCE_FLOAT -#include "param_float.h" -#else -#include "param.h" -#endif - -using namespace std; - -void ProgressBar (string str, double p, double total); -void ProgressBar (string str, double p, double total, double ratio); -std::istream& safeGetline(std::istream& is, std::string& t); - -bool ReadFile_snps (const string &file_snps, set<string> &setSnps); -bool ReadFile_log (const string &file_log, double &pheno_mean); - -bool ReadFile_bim (const string &file_bim, vector<SNPINFO> &snpInfo); -bool ReadFile_fam (const string &file_fam, vector<vector<int> > &indicator_pheno, vector<vector<double> > &pheno, map<string, int> &mapID2num, const vector<size_t> &p_column); - -bool ReadFile_cvt (const string &file_cvt, vector<int> &indicator_cvt, vector<vector<double> > &cvt, size_t &n_cvt); -bool ReadFile_anno (const string &file_bim, map<string, string> &mapRS2chr, map<string, long int> &mapRS2bp, map<string, double> &mapRS2cM); -bool ReadFile_pheno (const string &file_pheno, vector<vector<int> > &indicator_pheno, vector<vector<double> > &pheno, const vector<size_t> &p_column); -bool ReadFile_column (const string &file_pheno, vector<int> &indicator_idv, vector<double> &pheno, const int &p_column); - -bool ReadFile_geno (const string &file_geno, const set<string> &setSnps, const gsl_matrix *W, vector<int> &indicator_idv, vector<int> &indicator_snp, const double &maf_level, const double &miss_level, const double &hwe_level, const double &r2_level, map<string, string> &mapRS2chr, map<string, long int> &mapRS2bp, map<string, double> &mapRS2cM, vector<SNPINFO> &snpInfo, size_t &ns_test); -bool ReadFile_bed (const string &file_bed, const set<string> &setSnps, const gsl_matrix *W, vector<int> &indicator_idv, vector<int> &indicator_snp, vector<SNPINFO> &snpInfo, const double &maf_level, const double &miss_level, const double &hwe_level, const double &r2_level, size_t &ns_test); - -void ReadFile_kin (const string &file_kin, vector<int> &indicator_idv, map<string, int> &mapID2num, const size_t k_mode, bool &error, gsl_matrix *G); -void ReadFile_mk (const string &file_mk, vector<int> &indicator_idv, map<string, int> &mapID2num, const size_t k_mode, bool &error, gsl_matrix *G); -void ReadFile_eigenU (const string &file_u, bool &error, gsl_matrix *U); -void ReadFile_eigenD (const string &file_d, bool &error, gsl_vector *eval); - -bool BimbamKin (const string &file_geno, vector<int> &indicator_snp, const int k_mode, const int display_pace, gsl_matrix *matrix_kin); -bool PlinkKin (const string &file_bed, vector<int> &indicator_snp, const int k_mode, const int display_pace, gsl_matrix *matrix_kin); - -bool ReadFile_geno (const string &file_geno, vector<int> &indicator_idv, vector<int> &indicator_snp, gsl_matrix *UtX, gsl_matrix *K, const bool calc_K); -bool ReadFile_bed (const string &file_bed, vector<int> &indicator_idv, vector<int> &indicator_snp, gsl_matrix *UtX, gsl_matrix *K, const bool calc_K); - -bool ReadFile_est (const string &file_est, const vector<size_t> &est_column, map<string, double> &mapRS2est); - -bool CountFileLines (const string &file_input, size_t &n_lines); - -bool ReadFile_gene (const string &file_gene, vector<double> &vec_read, vector<SNPINFO> &snpInfo, size_t &ng_total); - -#endif - - - - - - - diff --git a/lapack.cpp b/lapack.cpp deleted file mode 100644 index 83d5290..0000000 --- a/lapack.cpp +++ /dev/null @@ -1,609 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#include <iostream> -#include <cmath> -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" - -using namespace std; - -extern "C" void sgemm_(char *TRANSA, char *TRANSB, int *M, int *N, int *K, float *ALPHA, float *A, int *LDA, float *B, int *LDB, float *BETA, float *C, int *LDC); -extern "C" void spotrf_(char *UPLO, int *N, float *A, int *LDA, int *INFO); -extern "C" void spotrs_(char *UPLO, int *N, int *NRHS, float *A, int *LDA, float *B, int *LDB, int *INFO); -extern "C" void ssyev_(char* JOBZ, char* UPLO, int *N, float *A, int *LDA, float *W, float *WORK, int *LWORK, int *INFO); -extern "C" void ssyevr_(char* JOBZ, char *RANGE, char* UPLO, int *N, float *A, int *LDA, float *VL, float *VU, int *IL, int *IU, float *ABSTOL, int *M, float *W, float *Z, int *LDZ, int *ISUPPZ, float *WORK, int *LWORK, int *IWORK, int *LIWORK, int *INFO); - -extern "C" void dgemm_(char *TRANSA, char *TRANSB, int *M, int *N, int *K, double *ALPHA, double *A, int *LDA, double *B, int *LDB, double *BETA, double *C, int *LDC); -extern "C" void dpotrf_(char *UPLO, int *N, double *A, int *LDA, int *INFO); -extern "C" void dpotrs_(char *UPLO, int *N, int *NRHS, double *A, int *LDA, double *B, int *LDB, int *INFO); -extern "C" void dsyev_(char* JOBZ, char* UPLO, int *N, double *A, int *LDA, double *W, double *WORK, int *LWORK, int *INFO); -extern "C" void dsyevr_(char* JOBZ, char *RANGE, char* UPLO, int *N, double *A, int *LDA, double *VL, double *VU, int *IL, int *IU, double *ABSTOL, int *M, double *W, double *Z, int *LDZ, int *ISUPPZ, double *WORK, int *LWORK, int *IWORK, int *LIWORK, int *INFO); - - -//cholesky decomposition, A is distroyed -void lapack_float_cholesky_decomp (gsl_matrix_float *A) -{ - int N=A->size1, LDA=A->size1, INFO; - char UPLO='L'; - - if (N!=(int)A->size2) {cout<<"Matrix needs to be symmetric and same dimension in lapack_cholesky_decomp."<<endl; return;} - - spotrf_(&UPLO, &N, A->data, &LDA, &INFO); - if (INFO!=0) {cout<<"Cholesky decomposition unsuccessful in lapack_cholesky_decomp."<<endl; return;} - - return; -} - -//cholesky decomposition, A is distroyed -void lapack_cholesky_decomp (gsl_matrix *A) -{ - int N=A->size1, LDA=A->size1, INFO; - char UPLO='L'; - - if (N!=(int)A->size2) {cout<<"Matrix needs to be symmetric and same dimension in lapack_cholesky_decomp."<<endl; return;} - - dpotrf_(&UPLO, &N, A->data, &LDA, &INFO); - if (INFO!=0) {cout<<"Cholesky decomposition unsuccessful in lapack_cholesky_decomp."<<endl; return;} - - return; -} - -//cholesky solve, A is decomposed, -void lapack_float_cholesky_solve (gsl_matrix_float *A, const gsl_vector_float *b, gsl_vector_float *x) -{ - int N=A->size1, NRHS=1, LDA=A->size1, LDB=b->size, INFO; - char UPLO='L'; - - if (N!=(int)A->size2 || N!=LDB) {cout<<"Matrix needs to be symmetric and same dimension in lapack_cholesky_solve."<<endl; return;} - - gsl_vector_float_memcpy (x, b); - spotrs_(&UPLO, &N, &NRHS, A->data, &LDA, x->data, &LDB, &INFO); - if (INFO!=0) {cout<<"Cholesky solve unsuccessful in lapack_cholesky_solve."<<endl; return;} - - return; -} - -//cholesky solve, A is decomposed, -void lapack_cholesky_solve (gsl_matrix *A, const gsl_vector *b, gsl_vector *x) -{ - int N=A->size1, NRHS=1, LDA=A->size1, LDB=b->size, INFO; - char UPLO='L'; - - if (N!=(int)A->size2 || N!=LDB) {cout<<"Matrix needs to be symmetric and same dimension in lapack_cholesky_solve."<<endl; return;} - - gsl_vector_memcpy (x, b); - dpotrs_(&UPLO, &N, &NRHS, A->data, &LDA, x->data, &LDB, &INFO); - if (INFO!=0) {cout<<"Cholesky solve unsuccessful in lapack_cholesky_solve."<<endl; return;} - - return; -} - - -void lapack_sgemm (char *TransA, char *TransB, float alpha, const gsl_matrix_float *A, const gsl_matrix_float *B, float beta, gsl_matrix_float *C) -{ - int M, N, K1, K2, LDA=A->size1, LDB=B->size1, LDC=C->size2; - - if (*TransA=='N' || *TransA=='n') {M=A->size1; K1=A->size2;} - else if (*TransA=='T' || *TransA=='t') {M=A->size2; K1=A->size1;} - else {cout<<"need 'N' or 'T' in lapack_sgemm"<<endl; return;} - - if (*TransB=='N' || *TransB=='n') {N=B->size2; K2=B->size1;} - else if (*TransB=='T' || *TransB=='t') {N=B->size1; K2=B->size2;} - else {cout<<"need 'N' or 'T' in lapack_sgemm"<<endl; return;} - - if (K1!=K2) {cout<<"A and B not compatible in lapack_sgemm"<<endl; return;} - if (C->size1!=(size_t)M || C->size2!=(size_t)N) {cout<<"C not compatible in lapack_sgemm"<<endl; return;} - - gsl_matrix_float *A_t=gsl_matrix_float_alloc (A->size2, A->size1); - gsl_matrix_float_transpose_memcpy (A_t, A); - gsl_matrix_float *B_t=gsl_matrix_float_alloc (B->size2, B->size1); - gsl_matrix_float_transpose_memcpy (B_t, B); - gsl_matrix_float *C_t=gsl_matrix_float_alloc (C->size2, C->size1); - gsl_matrix_float_transpose_memcpy (C_t, C); - - sgemm_(TransA, TransB, &M, &N, &K1, &alpha, A_t->data, &LDA, B_t->data, &LDB, &beta, C_t->data, &LDC); - gsl_matrix_float_transpose_memcpy (C, C_t); - - gsl_matrix_float_free (A_t); - gsl_matrix_float_free (B_t); - gsl_matrix_float_free (C_t); - return; -} - - - -void lapack_dgemm (char *TransA, char *TransB, double alpha, const gsl_matrix *A, const gsl_matrix *B, double beta, gsl_matrix *C) -{ - int M, N, K1, K2, LDA=A->size1, LDB=B->size1, LDC=C->size2; - - if (*TransA=='N' || *TransA=='n') {M=A->size1; K1=A->size2;} - else if (*TransA=='T' || *TransA=='t') {M=A->size2; K1=A->size1;} - else {cout<<"need 'N' or 'T' in lapack_dgemm"<<endl; return;} - - if (*TransB=='N' || *TransB=='n') {N=B->size2; K2=B->size1;} - else if (*TransB=='T' || *TransB=='t') {N=B->size1; K2=B->size2;} - else {cout<<"need 'N' or 'T' in lapack_dgemm"<<endl; return;} - - if (K1!=K2) {cout<<"A and B not compatible in lapack_dgemm"<<endl; return;} - if (C->size1!=(size_t)M || C->size2!=(size_t)N) {cout<<"C not compatible in lapack_dgemm"<<endl; return;} - - gsl_matrix *A_t=gsl_matrix_alloc (A->size2, A->size1); - gsl_matrix_transpose_memcpy (A_t, A); - gsl_matrix *B_t=gsl_matrix_alloc (B->size2, B->size1); - gsl_matrix_transpose_memcpy (B_t, B); - gsl_matrix *C_t=gsl_matrix_alloc (C->size2, C->size1); - gsl_matrix_transpose_memcpy (C_t, C); - - dgemm_(TransA, TransB, &M, &N, &K1, &alpha, A_t->data, &LDA, B_t->data, &LDB, &beta, C_t->data, &LDC); - - gsl_matrix_transpose_memcpy (C, C_t); - - gsl_matrix_free (A_t); - gsl_matrix_free (B_t); - gsl_matrix_free (C_t); - return; -} - - - -//eigen value decomposition, matrix A is destroyed, float seems to have problem with large matrices (in mac) -void lapack_float_eigen_symmv (gsl_matrix_float *A, gsl_vector_float *eval, gsl_matrix_float *evec, const size_t flag_largematrix) -{ - if (flag_largematrix==1) { - int N=A->size1, LDA=A->size1, INFO, LWORK=-1; - char JOBZ='V', UPLO='L'; - - if (N!=(int)A->size2 || N!=(int)eval->size) {cout<<"Matrix needs to be symmetric and same dimension in lapack_eigen_symmv."<<endl; return;} - - // float temp[1]; - // ssyev_(&JOBZ, &UPLO, &N, A->data, &LDA, eval->data, temp, &LWORK, &INFO); - // if (INFO!=0) {cout<<"Work space estimate unsuccessful in lapack_eigen_symmv."<<endl; return;} - // LWORK=(int)temp[0]; - - LWORK=3*N; - float *WORK=new float [LWORK]; - ssyev_(&JOBZ, &UPLO, &N, A->data, &LDA, eval->data, WORK, &LWORK, &INFO); - if (INFO!=0) {cout<<"Eigen decomposition unsuccessful in lapack_eigen_symmv."<<endl; return;} - - gsl_matrix_float_view A_sub=gsl_matrix_float_submatrix(A, 0, 0, N, N); - gsl_matrix_float_memcpy (evec, &A_sub.matrix); - gsl_matrix_float_transpose (evec); - - delete [] WORK; - } else { - int N=A->size1, LDA=A->size1, LDZ=A->size1, INFO, LWORK=-1, LIWORK=-1; - char JOBZ='V', UPLO='L', RANGE='A'; - float ABSTOL=1.0E-7; - - //VL, VU, IL, IU are not referenced; M equals N if RANGE='A' - float VL=0.0, VU=0.0; - int IL=0, IU=0, M; - - if (N!=(int)A->size2 || N!=(int)eval->size) {cout<<"Matrix needs to be symmetric and same dimension in lapack_float_eigen_symmv."<<endl; return;} - - int *ISUPPZ=new int [2*N]; - - float WORK_temp[1]; - int IWORK_temp[1]; - ssyevr_(&JOBZ, &RANGE, &UPLO, &N, A->data, &LDA, &VL, &VU, &IL, &IU, &ABSTOL, &M, eval->data, evec->data, &LDZ, ISUPPZ, WORK_temp, &LWORK, IWORK_temp, &LIWORK, &INFO); - if (INFO!=0) {cout<<"Work space estimate unsuccessful in lapack_float_eigen_symmv."<<endl; return;} - LWORK=(int)WORK_temp[0]; LIWORK=(int)IWORK_temp[0]; - - //LWORK=26*N; - //LIWORK=10*N; - float *WORK=new float [LWORK]; - int *IWORK=new int [LIWORK]; - - ssyevr_(&JOBZ, &RANGE, &UPLO, &N, A->data, &LDA, &VL, &VU, &IL, &IU, &ABSTOL, &M, eval->data, evec->data, &LDZ, ISUPPZ, WORK, &LWORK, IWORK, &LIWORK, &INFO); - if (INFO!=0) {cout<<"Eigen decomposition unsuccessful in lapack_float_eigen_symmv."<<endl; return;} - - gsl_matrix_float_transpose (evec); - - delete [] ISUPPZ; - delete [] WORK; - delete [] IWORK; - } - - - return; -} - - - -//eigen value decomposition, matrix A is destroyed -void lapack_eigen_symmv (gsl_matrix *A, gsl_vector *eval, gsl_matrix *evec, const size_t flag_largematrix) -{ - if (flag_largematrix==1) { - int N=A->size1, LDA=A->size1, INFO, LWORK=-1; - char JOBZ='V', UPLO='L'; - - if (N!=(int)A->size2 || N!=(int)eval->size) {cout<<"Matrix needs to be symmetric and same dimension in lapack_eigen_symmv."<<endl; return;} - - // double temp[1]; - // dsyev_(&JOBZ, &UPLO, &N, A->data, &LDA, eval->data, temp, &LWORK, &INFO); - // if (INFO!=0) {cout<<"Work space estimate unsuccessful in lapack_eigen_symmv."<<endl; return;} - // LWORK=(int)temp[0]; - - LWORK=3*N; - double *WORK=new double [LWORK]; - dsyev_(&JOBZ, &UPLO, &N, A->data, &LDA, eval->data, WORK, &LWORK, &INFO); - if (INFO!=0) {cout<<"Eigen decomposition unsuccessful in lapack_eigen_symmv."<<endl; return;} - - gsl_matrix_view A_sub=gsl_matrix_submatrix(A, 0, 0, N, N); - gsl_matrix_memcpy (evec, &A_sub.matrix); - gsl_matrix_transpose (evec); - - delete [] WORK; - } else { - int N=A->size1, LDA=A->size1, LDZ=A->size1, INFO, LWORK=-1, LIWORK=-1; - char JOBZ='V', UPLO='L', RANGE='A'; - double ABSTOL=1.0E-7; - - //VL, VU, IL, IU are not referenced; M equals N if RANGE='A' - double VL=0.0, VU=0.0; - int IL=0, IU=0, M; - - if (N!=(int)A->size2 || N!=(int)eval->size) {cout<<"Matrix needs to be symmetric and same dimension in lapack_eigen_symmv."<<endl; return;} - - int *ISUPPZ=new int [2*N]; - - double WORK_temp[1]; - int IWORK_temp[1]; - - dsyevr_(&JOBZ, &RANGE, &UPLO, &N, A->data, &LDA, &VL, &VU, &IL, &IU, &ABSTOL, &M, eval->data, evec->data, &LDZ, ISUPPZ, WORK_temp, &LWORK, IWORK_temp, &LIWORK, &INFO); - if (INFO!=0) {cout<<"Work space estimate unsuccessful in lapack_eigen_symmv."<<endl; return;} - LWORK=(int)WORK_temp[0]; LIWORK=(int)IWORK_temp[0]; - - //LWORK=26*N; - //LIWORK=10*N; - double *WORK=new double [LWORK]; - int *IWORK=new int [LIWORK]; - - dsyevr_(&JOBZ, &RANGE, &UPLO, &N, A->data, &LDA, &VL, &VU, &IL, &IU, &ABSTOL, &M, eval->data, evec->data, &LDZ, ISUPPZ, WORK, &LWORK, IWORK, &LIWORK, &INFO); - if (INFO!=0) {cout<<"Eigen decomposition unsuccessful in lapack_eigen_symmv."<<endl; return;} - - gsl_matrix_transpose (evec); - - delete [] ISUPPZ; - delete [] WORK; - delete [] IWORK; - } - - return; -} - -//DO NOT set eigen values to be positive -double EigenDecomp (gsl_matrix *G, gsl_matrix *U, gsl_vector *eval, const size_t flag_largematrix) -{ -#ifdef WITH_LAPACK - lapack_eigen_symmv (G, eval, U, flag_largematrix); -#else - gsl_eigen_symmv_workspace *w=gsl_eigen_symmv_alloc (G->size1); - gsl_eigen_symmv (G, eval, U, w); - gsl_eigen_symmv_free (w); -#endif - /* - for (size_t i=0; i<eval->size; ++i) { - if (gsl_vector_get (eval, i)<1e-10) { -// cout<<gsl_vector_get (eval, i)<<endl; - gsl_vector_set (eval, i, 0); - } - } - */ - //calculate track_G=mean(diag(G)) - double d=0.0; - for (size_t i=0; i<eval->size; ++i) { - d+=gsl_vector_get(eval, i); - } - d/=(double)eval->size; - - return d; -} - - -//DO NOT set eigen values to be positive -double EigenDecomp (gsl_matrix_float *G, gsl_matrix_float *U, gsl_vector_float *eval, const size_t flag_largematrix) -{ -#ifdef WITH_LAPACK - lapack_float_eigen_symmv (G, eval, U, flag_largematrix); -#else - //gsl doesn't provide float precision eigen decomposition; plus, float precision eigen decomposition in lapack may not work on OS 10.4 - //first change to double precision - gsl_matrix *G_double=gsl_matrix_alloc (G->size1, G->size2); - gsl_matrix *U_double=gsl_matrix_alloc (U->size1, U->size2); - gsl_vector *eval_double=gsl_vector_alloc (eval->size); - for (size_t i=0; i<G->size1; i++) { - for (size_t j=0; j<G->size2; j++) { - gsl_matrix_set(G_double, i, j, gsl_matrix_float_get(G, i, j)); - } - } - gsl_eigen_symmv_workspace *w_space=gsl_eigen_symmv_alloc (G->size1); - gsl_eigen_symmv (G_double, eval_double, U_double, w_space); - gsl_eigen_symmv_free (w_space); - - //change back to float precision - for (size_t i=0; i<G->size1; i++) { - for (size_t j=0; j<G->size2; j++) { - gsl_matrix_float_set(K, i, j, gsl_matrix_get(G_double, i, j)); - } - } - for (size_t i=0; i<U->size1; i++) { - for (size_t j=0; j<U->size2; j++) { - gsl_matrix_float_set(U, i, j, gsl_matrix_get(U_double, i, j)); - } - } - for (size_t i=0; i<eval->size; i++) { - gsl_vector_float_set(eval, i, gsl_vector_get(eval_double, i)); - } - - //delete double precision matrices - gsl_matrix_free (G_double); - gsl_matrix_free (U_double); - gsl_vector_free (eval_double); -#endif - /* - for (size_t i=0; i<eval->size; ++i) { - if (gsl_vector_float_get (eval, i)<1e-10) { - gsl_vector_float_set (eval, i, 0); - } - } - */ - //calculate track_G=mean(diag(G)) - double d=0.0; - for (size_t i=0; i<eval->size; ++i) { - d+=gsl_vector_float_get(eval, i); - } - d/=(double)eval->size; - - return d; -} - - -double CholeskySolve(gsl_matrix *Omega, gsl_vector *Xty, gsl_vector *OiXty) -{ - double logdet_O=0.0; - -#ifdef WITH_LAPACK - lapack_cholesky_decomp(Omega); - for (size_t i=0; i<Omega->size1; ++i) { - logdet_O+=log(gsl_matrix_get (Omega, i, i)); - } - logdet_O*=2.0; - lapack_cholesky_solve(Omega, Xty, OiXty); -#else - int status = gsl_linalg_cholesky_decomp(Omega); - if(status == GSL_EDOM) { - cout << "## non-positive definite matrix" << endl; - // exit(0); - } - - for (size_t i=0; i<Omega->size1; ++i) { - logdet_O+=log(gsl_matrix_get (Omega, i, i)); - } - logdet_O*=2.0; - - gsl_vector_memcpy (OiXty, Xty); - gsl_blas_dtrsv(CblasLower, CblasNoTrans, CblasNonUnit, Omega, OiXty); - gsl_blas_dtrsv(CblasUpper, CblasNoTrans, CblasNonUnit, Omega, OiXty); - // gsl_linalg_cholesky_solve(XtX, Xty, iXty); -#endif - - return logdet_O; -} - - -double CholeskySolve(gsl_matrix_float *Omega, gsl_vector_float *Xty, gsl_vector_float *OiXty) -{ - double logdet_O=0.0; - -#ifdef WITH_LAPACK - lapack_float_cholesky_decomp(Omega); - for (size_t i=0; i<Omega->size1; ++i) { - logdet_O+=log(gsl_matrix_float_get (Omega, i, i)); - } - logdet_O*=2.0; - lapack_float_cholesky_solve(Omega, Xty, OiXty); -#else - gsl_matrix *Omega_double=gsl_matrix_alloc (Omega->size1, Omega->size2); - double d; - for (size_t i=0; i<Omega->size1; ++i) { - for (size_t j=0; j<Omega->size2; ++j) { - d=(double)gsl_matrix_float_get (Omega, i, j); - gsl_matrix_set (Omega_double, i, j, d); - } - } - - int status = gsl_linalg_cholesky_decomp(Omega_double); - if(status == GSL_EDOM) { - cout << "## non-positive definite matrix" << endl; - // exit(0); - } - - for (size_t i=0; i<Omega->size1; ++i) { - for (size_t j=0; j<Omega->size2; ++j) { - d=gsl_matrix_get (Omega_double, i, j); - if (j==i) {logdet_O+=log(d);} - gsl_matrix_float_set (Omega, i, j, (float)d); - } - } - logdet_O*=2.0; - - gsl_vector_float_memcpy (OiXty, Xty); - gsl_blas_strsv(CblasLower, CblasNoTrans, CblasNonUnit, Omega, OiXty); - gsl_blas_strsv(CblasUpper, CblasNoTrans, CblasNonUnit, Omega, OiXty); - // gsl_linalg_cholesky_solve(XtX, Xty, iXty); - - gsl_matrix_free (Omega_double); -#endif - - return logdet_O; -} - - -//LU decomposition -void LUDecomp (gsl_matrix *LU, gsl_permutation *p, int *signum) -{ - gsl_linalg_LU_decomp (LU, p, signum); - return; -} - -void LUDecomp (gsl_matrix_float *LU, gsl_permutation *p, int *signum) -{ - gsl_matrix *LU_double=gsl_matrix_alloc (LU->size1, LU->size2); - - //copy float matrix to double - for (size_t i=0; i<LU->size1; i++) { - for (size_t j=0; j<LU->size2; j++) { - gsl_matrix_set (LU_double, i, j, gsl_matrix_float_get(LU, i, j)); - } - } - - //LU decomposition - gsl_linalg_LU_decomp (LU_double, p, signum); - - //copy float matrix to double - for (size_t i=0; i<LU->size1; i++) { - for (size_t j=0; j<LU->size2; j++) { - gsl_matrix_float_set (LU, i, j, gsl_matrix_get(LU_double, i, j)); - } - } - - //free matrix - gsl_matrix_free (LU_double); - return; -} - - -//LU invert -void LUInvert (const gsl_matrix *LU, const gsl_permutation *p, gsl_matrix *inverse) -{ - gsl_linalg_LU_invert (LU, p, inverse); - return; -} - -void LUInvert (const gsl_matrix_float *LU, const gsl_permutation *p, gsl_matrix_float *inverse) -{ - gsl_matrix *LU_double=gsl_matrix_alloc (LU->size1, LU->size2); - gsl_matrix *inverse_double=gsl_matrix_alloc (inverse->size1, inverse->size2); - - //copy float matrix to double - for (size_t i=0; i<LU->size1; i++) { - for (size_t j=0; j<LU->size2; j++) { - gsl_matrix_set (LU_double, i, j, gsl_matrix_float_get(LU, i, j)); - } - } - - //LU decomposition - gsl_linalg_LU_invert (LU_double, p, inverse_double); - - //copy float matrix to double - for (size_t i=0; i<inverse->size1; i++) { - for (size_t j=0; j<inverse->size2; j++) { - gsl_matrix_float_set (inverse, i, j, gsl_matrix_get(inverse_double, i, j)); - } - } - - //free matrix - gsl_matrix_free (LU_double); - gsl_matrix_free (inverse_double); - return; -} - -//LU lndet -double LULndet (gsl_matrix *LU) -{ - double d; - d=gsl_linalg_LU_lndet (LU); - return d; -} - -double LULndet (gsl_matrix_float *LU) -{ - gsl_matrix *LU_double=gsl_matrix_alloc (LU->size1, LU->size2); - double d; - - //copy float matrix to double - for (size_t i=0; i<LU->size1; i++) { - for (size_t j=0; j<LU->size2; j++) { - gsl_matrix_set (LU_double, i, j, gsl_matrix_float_get(LU, i, j)); - } - } - - //LU decomposition - d=gsl_linalg_LU_lndet (LU_double); - - //copy float matrix to double - /* - for (size_t i=0; i<LU->size1; i++) { - for (size_t j=0; j<LU->size2; j++) { - gsl_matrix_float_set (LU, i, j, gsl_matrix_get(LU_double, i, j)); - } - } - */ - //free matrix - gsl_matrix_free (LU_double); - return d; -} - - -//LU solve -void LUSolve (const gsl_matrix *LU, const gsl_permutation *p, const gsl_vector *b, gsl_vector *x) -{ - gsl_linalg_LU_solve (LU, p, b, x); - return; -} - -void LUSolve (const gsl_matrix_float *LU, const gsl_permutation *p, const gsl_vector_float *b, gsl_vector_float *x) -{ - gsl_matrix *LU_double=gsl_matrix_alloc (LU->size1, LU->size2); - gsl_vector *b_double=gsl_vector_alloc (b->size); - gsl_vector *x_double=gsl_vector_alloc (x->size); - - //copy float matrix to double - for (size_t i=0; i<LU->size1; i++) { - for (size_t j=0; j<LU->size2; j++) { - gsl_matrix_set (LU_double, i, j, gsl_matrix_float_get(LU, i, j)); - } - } - - for (size_t i=0; i<b->size; i++) { - gsl_vector_set (b_double, i, gsl_vector_float_get(b, i)); - } - - for (size_t i=0; i<x->size; i++) { - gsl_vector_set (x_double, i, gsl_vector_float_get(x, i)); - } - - //LU decomposition - gsl_linalg_LU_solve (LU_double, p, b_double, x_double); - - //copy float matrix to double - for (size_t i=0; i<x->size; i++) { - gsl_vector_float_set (x, i, gsl_vector_get(x_double, i)); - } - - //free matrix - gsl_matrix_free (LU_double); - gsl_vector_free (b_double); - gsl_vector_free (x_double); - return; -} - - diff --git a/lapack.h b/lapack.h deleted file mode 100644 index cb7b156..0000000 --- a/lapack.h +++ /dev/null @@ -1,53 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __LAPACK_H__ -#define __LAPACK_H__ - - - -using namespace std; - - -void lapack_float_cholesky_decomp (gsl_matrix_float *A); -void lapack_cholesky_decomp (gsl_matrix *A); -void lapack_float_cholesky_solve (gsl_matrix_float *A, const gsl_vector_float *b, gsl_vector_float *x); -void lapack_cholesky_solve (gsl_matrix *A, const gsl_vector *b, gsl_vector *x); -void lapack_sgemm (char *TransA, char *TransB, float alpha, const gsl_matrix_float *A, const gsl_matrix_float *B, float beta, gsl_matrix_float *C); -void lapack_dgemm (char *TransA, char *TransB, double alpha, const gsl_matrix *A, const gsl_matrix *B, double beta, gsl_matrix *C); -void lapack_float_eigen_symmv (gsl_matrix_float *A, gsl_vector_float *eval, gsl_matrix_float *evec, const size_t flag_largematrix); -void lapack_eigen_symmv (gsl_matrix *A, gsl_vector *eval, gsl_matrix *evec, const size_t flag_largematrix); - -double EigenDecomp (gsl_matrix *G, gsl_matrix *U, gsl_vector *eval, const size_t flag_largematrix); -double EigenDecomp (gsl_matrix_float *G, gsl_matrix_float *U, gsl_vector_float *eval, const size_t flag_largematrix); - -double CholeskySolve(gsl_matrix *Omega, gsl_vector *Xty, gsl_vector *OiXty); -double CholeskySolve(gsl_matrix_float *Omega, gsl_vector_float *Xty, gsl_vector_float *OiXty); - -void LUDecomp (gsl_matrix *LU, gsl_permutation *p, int *signum); -void LUDecomp (gsl_matrix_float *LU, gsl_permutation *p, int *signum); -void LUInvert (const gsl_matrix *LU, const gsl_permutation *p, gsl_matrix *inverse); -void LUInvert (const gsl_matrix_float *LU, const gsl_permutation *p, gsl_matrix_float *inverse); -double LULndet (gsl_matrix *LU); -double LULndet (gsl_matrix_float *LU); -void LUSolve (const gsl_matrix *LU, const gsl_permutation *p, const gsl_vector *b, gsl_vector *x); -void LUSolve (const gsl_matrix_float *LU, const gsl_permutation *p, const gsl_vector_float *b, gsl_vector_float *x); -#endif - - - diff --git a/lm.cpp b/lm.cpp deleted file mode 100644 index 7577d0a..0000000 --- a/lm.cpp +++ /dev/null @@ -1,572 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - - - -#include <iostream> -#include <fstream> -#include <sstream> - -#include <iomanip> -#include <cmath> -#include <iostream> -#include <stdio.h> -#include <stdlib.h> -#include <bitset> -#include <cstring> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" - - -#include "gsl/gsl_cdf.h" -#include "gsl/gsl_roots.h" -#include "gsl/gsl_min.h" -#include "gsl/gsl_integration.h" - -#include "gzstream.h" -#include "lapack.h" - -#ifdef FORCE_FLOAT -#include "lm_float.h" -#else -#include "lm.h" -#endif - - -using namespace std; - - - - - -void LM::CopyFromParam (PARAM &cPar) -{ - a_mode=cPar.a_mode; - d_pace=cPar.d_pace; - - file_bfile=cPar.file_bfile; - file_geno=cPar.file_geno; - file_out=cPar.file_out; - path_out=cPar.path_out; - file_gene=cPar.file_gene; - - time_opt=0.0; - - ni_total=cPar.ni_total; - ns_total=cPar.ns_total; - ni_test=cPar.ni_test; - ns_test=cPar.ns_test; - n_cvt=cPar.n_cvt; - - ng_total=cPar.ng_total; - ng_test=0; - - indicator_idv=cPar.indicator_idv; - indicator_snp=cPar.indicator_snp; - snpInfo=cPar.snpInfo; - - return; -} - - -void LM::CopyToParam (PARAM &cPar) -{ - cPar.time_opt=time_opt; - - cPar.ng_test=ng_test; - - return; -} - - - -void LM::WriteFiles () -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".assoc.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - if (!file_gene.empty()) { - outfile<<"geneID"<<"\t"; - - if (a_mode==51) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_wald"<<endl; - } else if (a_mode==52) { - outfile<<"p_lrt"<<endl; - } else if (a_mode==53) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_score"<<endl; - } else if (a_mode==54) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_wald"<<"\t"<<"p_lrt"<<"\t"<<"p_score"<<endl; - } else {} - - for (vector<SUMSTAT>::size_type t=0; t<sumStat.size(); ++t) { - outfile<<snpInfo[t].rs_number<<"\t"; - - if (a_mode==51) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_wald <<endl; - } else if (a_mode==52) { - outfile<<scientific<<setprecision(6)<<"\t"<<sumStat[t].p_lrt<<endl; - } else if (a_mode==53) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_score<<endl; - } else if (a_mode==54) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_wald <<"\t"<<sumStat[t].p_lrt<<"\t"<<sumStat[t].p_score<<endl; - } else {} - } - } else { - outfile<<"chr"<<"\t"<<"rs"<<"\t"<<"ps"<<"\t"<<"n_miss"<<"\t"<<"allele1"<<"\t"<<"allele0"<<"\t"<<"af"<<"\t"; - - if (a_mode==51) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_wald"<<endl; - } else if (a_mode==52) { - outfile<<"p_lrt"<<endl; - } else if (a_mode==53) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_score"<<endl; - } else if (a_mode==54) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_wald"<<"\t"<<"p_lrt"<<"\t"<<"p_score"<<endl; - } else {} - - size_t t=0; - for (size_t i=0; i<snpInfo.size(); ++i) { - if (indicator_snp[i]==0) {continue;} - - outfile<<snpInfo[i].chr<<"\t"<<snpInfo[i].rs_number<<"\t"<<snpInfo[i].base_position<<"\t"<<snpInfo[i].n_miss<<"\t"<<snpInfo[i].a_minor<<"\t"<<snpInfo[i].a_major<<"\t"<<fixed<<setprecision(3)<<snpInfo[i].maf<<"\t"; - - if (a_mode==51) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_wald <<endl; - } else if (a_mode==52) { - outfile<<scientific<<setprecision(6)<<sumStat[t].p_lrt<<endl; - } else if (a_mode==53) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_score<<endl; - } else if (a_mode==54) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_wald <<"\t"<<sumStat[t].p_lrt<<"\t"<<sumStat[t].p_score<<endl; - } else {} - t++; - } - } - - - outfile.close(); - outfile.clear(); - return; -} - - - - - -void CalcvPv(const gsl_matrix *WtWi, const gsl_vector *Wty, const gsl_vector *Wtx, const gsl_vector *y, const gsl_vector *x, double &xPwy, double &xPwx) -{ - size_t c_size=Wty->size; - double d; - - gsl_vector *WtWiWtx=gsl_vector_alloc (c_size); - - gsl_blas_ddot (x, x, &xPwx); - gsl_blas_ddot (x, y, &xPwy); - gsl_blas_dgemv (CblasNoTrans, 1.0, WtWi, Wtx, 0.0, WtWiWtx); - - gsl_blas_ddot (WtWiWtx, Wtx, &d); - xPwx-=d; - - gsl_blas_ddot (WtWiWtx, Wty, &d); - xPwy-=d; - - gsl_vector_free (WtWiWtx); - - return; -} - - -void CalcvPv(const gsl_matrix *WtWi, const gsl_vector *Wty, const gsl_vector *y, double &yPwy) -{ - size_t c_size=Wty->size; - double d; - - gsl_vector *WtWiWty=gsl_vector_alloc (c_size); - - gsl_blas_ddot (y, y, &yPwy); - gsl_blas_dgemv (CblasNoTrans, 1.0, WtWi, Wty, 0.0, WtWiWty); - - gsl_blas_ddot (WtWiWty, Wty, &d); - yPwy-=d; - - gsl_vector_free (WtWiWty); - - return; -} - - - -//calculate p values and beta/se in a linear model -void LmCalcP (const size_t test_mode, const double yPwy, const double xPwy, const double xPwx, const double df, const size_t n_size, double &beta, double &se, double &p_wald, double &p_lrt, double &p_score) -{ - double yPxy=yPwy-xPwy*xPwy/xPwx; - double se_wald, se_score; - - beta=xPwy/xPwx; - se_wald=sqrt(yPxy/(df*xPwx) ); - se_score=sqrt(yPwy/((double)n_size*xPwx) ); - - p_wald=gsl_cdf_fdist_Q (beta*beta/(se_wald*se_wald), 1.0, df); - p_score=gsl_cdf_fdist_Q (beta*beta/(se_score*se_score), 1.0, df); - p_lrt=gsl_cdf_chisq_Q ((double)n_size*(log(yPwy)-log(yPxy)), 1); - - if (test_mode==3) {se=se_score;} else {se=se_wald;} - - return; -} - - - - -void LM::AnalyzeGene (const gsl_matrix *W, const gsl_vector *x) -{ - ifstream infile (file_gene.c_str(), ifstream::in); - if (!infile) {cout<<"error reading gene expression file:"<<file_gene<<endl; return;} - - clock_t time_start=clock(); - - string line; - char *ch_ptr; - - double beta=0, se=0, p_wald=0, p_lrt=0, p_score=0; - int c_phen; - string rs; //gene id - double d; - - //calculate some basic quantities - double yPwy, xPwy, xPwx; - double df=(double)W->size1-(double)W->size2-1.0; - - gsl_vector *y=gsl_vector_alloc (W->size1); - - gsl_matrix *WtW=gsl_matrix_alloc (W->size2, W->size2); - gsl_matrix *WtWi=gsl_matrix_alloc (W->size2, W->size2); - gsl_vector *Wty=gsl_vector_alloc (W->size2); - gsl_vector *Wtx=gsl_vector_alloc (W->size2); - gsl_permutation * pmt=gsl_permutation_alloc (W->size2); - - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, W, W, 0.0, WtW); - int sig; - LUDecomp (WtW, pmt, &sig); - LUInvert (WtW, pmt, WtWi); - - gsl_blas_dgemv (CblasTrans, 1.0, W, x, 0.0, Wtx); - CalcvPv(WtWi, Wtx, x, xPwx); - - //header - getline(infile, line); - - for (size_t t=0; t<ng_total; t++) { - getline(infile, line); - if (t%d_pace==0 || t==ng_total-1) {ProgressBar ("Performing Analysis ", t, ng_total-1);} - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - rs=ch_ptr; - - c_phen=0; - for (size_t i=0; i<indicator_idv.size(); ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==0) {continue;} - - d=atof(ch_ptr); - gsl_vector_set(y, c_phen, d); - - c_phen++; - } - - //calculate statistics - time_start=clock(); - - gsl_blas_dgemv(CblasTrans, 1.0, W, y, 0.0, Wty); - CalcvPv(WtWi, Wtx, Wty, x, y, xPwy, yPwy); - LmCalcP (a_mode-50, yPwy, xPwy, xPwx, df, W->size1, beta, se, p_wald, p_lrt, p_score); - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - SUMSTAT SNPs={beta, se, 0.0, 0.0, p_wald, p_lrt, p_score}; - sumStat.push_back(SNPs); - } - cout<<endl; - - gsl_vector_free(y); - - gsl_matrix_free(WtW); - gsl_matrix_free(WtWi); - gsl_vector_free(Wty); - gsl_vector_free(Wtx); - gsl_permutation_free(pmt); - - infile.close(); - infile.clear(); - - return; -} - - - - -void LM::AnalyzeBimbam (const gsl_matrix *W, const gsl_vector *y) -{ - igzstream infile (file_geno.c_str(), igzstream::in); - // ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return;} - - clock_t time_start=clock(); - - string line; - char *ch_ptr; - - double beta=0, se=0, p_wald=0, p_lrt=0, p_score=0; - int n_miss, c_phen; - double geno, x_mean; - - //calculate some basic quantities - double yPwy, xPwy, xPwx; - double df=(double)W->size1-(double)W->size2-1.0; - - gsl_vector *x=gsl_vector_alloc (W->size1); - gsl_vector *x_miss=gsl_vector_alloc (W->size1); - - gsl_matrix *WtW=gsl_matrix_alloc (W->size2, W->size2); - gsl_matrix *WtWi=gsl_matrix_alloc (W->size2, W->size2); - gsl_vector *Wty=gsl_vector_alloc (W->size2); - gsl_vector *Wtx=gsl_vector_alloc (W->size2); - gsl_permutation * pmt=gsl_permutation_alloc (W->size2); - - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, W, W, 0.0, WtW); - int sig; - LUDecomp (WtW, pmt, &sig); - LUInvert (WtW, pmt, WtWi); - - gsl_blas_dgemv (CblasTrans, 1.0, W, y, 0.0, Wty); - CalcvPv(WtWi, Wty, y, yPwy); - - //start reading genotypes and analyze - for (size_t t=0; t<indicator_snp.size(); ++t) { - //if (t>1) {break;} - getline(infile, line); - if (t%d_pace==0 || t==(ns_total-1)) {ProgressBar ("Reading SNPs ", t, ns_total-1);} - if (indicator_snp[t]==0) {continue;} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - ch_ptr=strtok (NULL, " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - x_mean=0.0; c_phen=0; n_miss=0; - gsl_vector_set_zero(x_miss); - for (size_t i=0; i<ni_total; ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==0) {continue;} - - if (strcmp(ch_ptr, "NA")==0) {gsl_vector_set(x_miss, c_phen, 0.0); n_miss++;} - else { - geno=atof(ch_ptr); - - gsl_vector_set(x, c_phen, geno); - gsl_vector_set(x_miss, c_phen, 1.0); - x_mean+=geno; - } - c_phen++; - } - - x_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<ni_test; ++i) { - if (gsl_vector_get (x_miss, i)==0) {gsl_vector_set(x, i, x_mean);} - geno=gsl_vector_get(x, i); - if (x_mean>1) { - gsl_vector_set(x, i, 2-geno); - } - } - - //calculate statistics - time_start=clock(); - - gsl_blas_dgemv(CblasTrans, 1.0, W, x, 0.0, Wtx); - CalcvPv(WtWi, Wty, Wtx, y, x, xPwy, xPwx); - LmCalcP (a_mode-50, yPwy, xPwy, xPwx, df, W->size1, beta, se, p_wald, p_lrt, p_score); - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - SUMSTAT SNPs={beta, se, 0.0, 0.0, p_wald, p_lrt, p_score}; - sumStat.push_back(SNPs); - } - cout<<endl; - - gsl_vector_free(x); - gsl_vector_free(x_miss); - - gsl_matrix_free(WtW); - gsl_matrix_free(WtWi); - gsl_vector_free(Wty); - gsl_vector_free(Wtx); - gsl_permutation_free(pmt); - - infile.close(); - infile.clear(); - - return; -} - - - - - - - -void LM::AnalyzePlink (const gsl_matrix *W, const gsl_vector *y) -{ - string file_bed=file_bfile+".bed"; - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return;} - - clock_t time_start=clock(); - - char ch[1]; - bitset<8> b; - - double beta=0, se=0, p_wald=0, p_lrt=0, p_score=0; - int n_bit, n_miss, ci_total, ci_test; - double geno, x_mean; - - //calculate some basic quantities - double yPwy, xPwy, xPwx; - double df=(double)W->size1-(double)W->size2-1.0; - - gsl_vector *x=gsl_vector_alloc (W->size1); - - gsl_matrix *WtW=gsl_matrix_alloc (W->size2, W->size2); - gsl_matrix *WtWi=gsl_matrix_alloc (W->size2, W->size2); - gsl_vector *Wty=gsl_vector_alloc (W->size2); - gsl_vector *Wtx=gsl_vector_alloc (W->size2); - gsl_permutation * pmt=gsl_permutation_alloc (W->size2); - - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, W, W, 0.0, WtW); - int sig; - LUDecomp (WtW, pmt, &sig); - LUInvert (WtW, pmt, WtWi); - - gsl_blas_dgemv (CblasTrans, 1.0, W, y, 0.0, Wty); - CalcvPv(WtWi, Wty, y, yPwy); - - //calculate n_bit and c, the number of bit for each snp - if (ni_total%4==0) {n_bit=ni_total/4;} - else {n_bit=ni_total/4+1; } - - //print the first three majic numbers - for (int i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - - for (vector<SNPINFO>::size_type t=0; t<snpInfo.size(); ++t) { - if (t%d_pace==0 || t==snpInfo.size()-1) {ProgressBar ("Reading SNPs ", t, snpInfo.size()-1);} - if (indicator_snp[t]==0) {continue;} - - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - //read genotypes - x_mean=0.0; n_miss=0; ci_total=0; ci_test=0; - for (int i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && ci_total==(int)ni_total) {break;} - if (indicator_idv[ci_total]==0) {ci_total++; continue;} - - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(x, ci_test, 2); x_mean+=2.0; } - else {gsl_vector_set(x, ci_test, 1); x_mean+=1.0; } - } - else { - if (b[2*j+1]==1) {gsl_vector_set(x, ci_test, 0); } - else {gsl_vector_set(x, ci_test, -9); n_miss++; } - } - - ci_total++; - ci_test++; - } - } - - x_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<ni_test; ++i) { - geno=gsl_vector_get(x,i); - if (geno==-9) {gsl_vector_set(x, i, x_mean); geno=x_mean;} - if (x_mean>1) { - gsl_vector_set(x, i, 2-geno); - } - } - - //calculate statistics - time_start=clock(); - - gsl_blas_dgemv (CblasTrans, 1.0, W, x, 0.0, Wtx); - CalcvPv(WtWi, Wty, Wtx, y, x, xPwy, xPwx); - LmCalcP (a_mode-50, yPwy, xPwy, xPwx, df, W->size1, beta, se, p_wald, p_lrt, p_score); - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - SUMSTAT SNPs={beta, se, 0.0, 0.0, p_wald, p_lrt, p_score}; - sumStat.push_back(SNPs); - } - cout<<endl; - - gsl_vector_free(x); - - gsl_matrix_free(WtW); - gsl_matrix_free(WtWi); - gsl_vector_free(Wty); - gsl_vector_free(Wtx); - gsl_permutation_free(pmt); - - infile.close(); - infile.clear(); - - return; -} - - - -//make sure that both y and X are centered already -void MatrixCalcLmLR (const gsl_matrix *X, const gsl_vector *y, vector<pair<size_t, double> > &pos_loglr) -{ - double yty, xty, xtx, log_lr; - gsl_blas_ddot(y, y, &yty); - - for (size_t i=0; i<X->size2; ++i) { - gsl_vector_const_view X_col=gsl_matrix_const_column (X, i); - gsl_blas_ddot(&X_col.vector, &X_col.vector, &xtx); - gsl_blas_ddot(&X_col.vector, y, &xty); - - log_lr=0.5*(double)y->size*(log(yty)-log(yty-xty*xty/xtx)); - pos_loglr.push_back(make_pair(i,log_lr) ); - } - - return; -} diff --git a/lm.h b/lm.h deleted file mode 100644 index ceec060..0000000 --- a/lm.h +++ /dev/null @@ -1,75 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - -#ifndef __LM_H__ -#define __LM_H__ - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - - -#ifdef FORCE_FLOAT -#include "param_float.h" -#include "io_float.h" -#else -#include "param.h" -#include "io.h" -#endif - -using namespace std; - - -class LM { - -public: - // IO related parameters - int a_mode; //analysis mode, 50+1/2/3/4 for Frequentist tests - size_t d_pace; //display pace - - string file_bfile; - string file_geno; - string file_out; - string path_out; - - string file_gene; - - // Summary statistics - size_t ni_total, ni_test; //number of individuals - size_t ns_total, ns_test; //number of snps - size_t ng_total, ng_test; //number of genes - size_t n_cvt; - double time_opt; //time spent - - vector<int> indicator_idv; //indicator for individuals (phenotypes), 0 missing, 1 available for analysis - vector<int> indicator_snp; //sequence indicator for SNPs: 0 ignored because of (a) maf, (b) miss, (c) non-poly; 1 available for analysis - - vector<SNPINFO> snpInfo; //record SNP information - - // Not included in PARAM - vector<SUMSTAT> sumStat; //Output SNPSummary Data - - // Main functions - void CopyFromParam (PARAM &cPar); - void CopyToParam (PARAM &cPar); - void AnalyzeGene (const gsl_matrix *W, const gsl_vector *x); - void AnalyzePlink (const gsl_matrix *W, const gsl_vector *y); - void AnalyzeBimbam (const gsl_matrix *W, const gsl_vector *y); - void WriteFiles (); -}; -void MatrixCalcLmLR (const gsl_matrix *X, const gsl_vector *y, vector<pair<size_t, double> > &pos_loglr); -#endif diff --git a/lmm.cpp b/lmm.cpp deleted file mode 100644 index e0b4160..0000000 --- a/lmm.cpp +++ /dev/null @@ -1,1771 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - - - -#include <iostream> -#include <fstream> -#include <sstream> - -#include <iomanip> -#include <cmath> -#include <iostream> -#include <stdio.h> -#include <stdlib.h> -#include <bitset> -#include <cstring> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" - - -#include "gsl/gsl_cdf.h" -#include "gsl/gsl_roots.h" -#include "gsl/gsl_min.h" -#include "gsl/gsl_integration.h" - -#include "io.h" -#include "lapack.h" -#include "gzstream.h" - -#ifdef FORCE_FLOAT -#include "lmm_float.h" -#else -#include "lmm.h" -#endif - - -using namespace std; - - - - - -void LMM::CopyFromParam (PARAM &cPar) -{ - a_mode=cPar.a_mode; - d_pace=cPar.d_pace; - - file_bfile=cPar.file_bfile; - file_geno=cPar.file_geno; - file_out=cPar.file_out; - path_out=cPar.path_out; - file_gene=cPar.file_gene; - - l_min=cPar.l_min; - l_max=cPar.l_max; - n_region=cPar.n_region; - l_mle_null=cPar.l_mle_null; - logl_mle_H0=cPar.logl_mle_H0; - - time_UtX=0.0; - time_opt=0.0; - - ni_total=cPar.ni_total; - ns_total=cPar.ns_total; - ni_test=cPar.ni_test; - ns_test=cPar.ns_test; - n_cvt=cPar.n_cvt; - - ng_total=cPar.ng_total; - ng_test=0; - - indicator_idv=cPar.indicator_idv; - indicator_snp=cPar.indicator_snp; - snpInfo=cPar.snpInfo; - - return; -} - - -void LMM::CopyToParam (PARAM &cPar) -{ - cPar.time_UtX=time_UtX; - cPar.time_opt=time_opt; - - cPar.ng_test=ng_test; - - return; -} - - - -void LMM::WriteFiles () -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".assoc.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - if (!file_gene.empty()) { - outfile<<"geneID"<<"\t"; - - if (a_mode==1) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"l_remle"<<"\t"<<"p_wald"<<endl; - } else if (a_mode==2) { - outfile<<"l_mle"<<"\t"<<"p_lrt"<<endl; - } else if (a_mode==3) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_score"<<endl; - } else if (a_mode==4) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"l_remle"<<"\t"<<"l_mle"<<"\t"<<"p_wald"<<"\t"<<"p_lrt"<<"\t"<<"p_score"<<endl; - } else {} - - for (vector<SUMSTAT>::size_type t=0; t<sumStat.size(); ++t) { - outfile<<snpInfo[t].rs_number<<"\t"; - - if (a_mode==1) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].lambda_remle<<"\t"<<sumStat[t].p_wald <<endl; - } else if (a_mode==2) { - outfile<<scientific<<setprecision(6)<<sumStat[t].lambda_mle<<"\t"<<sumStat[t].p_lrt<<endl; - } else if (a_mode==3) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_score<<endl; - } else if (a_mode==4) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].lambda_remle<<"\t"<<sumStat[t].lambda_mle<<"\t"<<sumStat[t].p_wald <<"\t"<<sumStat[t].p_lrt<<"\t"<<sumStat[t].p_score<<endl; - } else {} - } - } else { - outfile<<"chr"<<"\t"<<"rs"<<"\t"<<"ps"<<"\t"<<"n_miss"<<"\t"<<"allele1"<<"\t"<<"allele0"<<"\t"<<"af"<<"\t"; - - if (a_mode==1) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"l_remle"<<"\t"<<"p_wald"<<endl; - } else if (a_mode==2) { - outfile<<"l_mle"<<"\t"<<"p_lrt"<<endl; - } else if (a_mode==3) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"p_score"<<endl; - } else if (a_mode==4) { - outfile<<"beta"<<"\t"<<"se"<<"\t"<<"l_remle"<<"\t"<<"l_mle"<<"\t"<<"p_wald"<<"\t"<<"p_lrt"<<"\t"<<"p_score"<<endl; - } else {} - - size_t t=0; - for (size_t i=0; i<snpInfo.size(); ++i) { - if (indicator_snp[i]==0) {continue;} - - outfile<<snpInfo[i].chr<<"\t"<<snpInfo[i].rs_number<<"\t"<<snpInfo[i].base_position<<"\t"<<snpInfo[i].n_miss<<"\t"<<snpInfo[i].a_minor<<"\t"<<snpInfo[i].a_major<<"\t"<<fixed<<setprecision(3)<<snpInfo[i].maf<<"\t"; - - if (a_mode==1) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].lambda_remle<<"\t"<<sumStat[t].p_wald <<endl; - } else if (a_mode==2) { - outfile<<scientific<<setprecision(6)<<sumStat[t].lambda_mle<<"\t"<<sumStat[t].p_lrt<<endl; - } else if (a_mode==3) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].p_score<<endl; - } else if (a_mode==4) { - outfile<<scientific<<setprecision(6)<<sumStat[t].beta<<"\t"<<sumStat[t].se<<"\t"<<sumStat[t].lambda_remle<<"\t"<<sumStat[t].lambda_mle<<"\t"<<sumStat[t].p_wald <<"\t"<<sumStat[t].p_lrt<<"\t"<<sumStat[t].p_score<<endl; - } else {} - t++; - } - } - - - outfile.close(); - outfile.clear(); - return; -} - - - - - - - - - - - -//map a number 1-(n_cvt+2) to an index between 0 and [(n_c+2)^2+(n_c+2)]/2-1 -size_t GetabIndex (const size_t a, const size_t b, const size_t n_cvt) { - if (a>n_cvt+2 || b>n_cvt+2 || a<=0 || b<=0) {cout<<"error in GetabIndex."<<endl; return 0;} - size_t index; - size_t l, h; - if (b>a) {l=a; h=b;} else {l=b; h=a;} - - size_t n=n_cvt+2; - index=(2*n-l+2)*(l-1)/2+h-l; - - return index; -} - - -void CalcPab (const size_t n_cvt, const size_t e_mode, const gsl_vector *Hi_eval, const gsl_matrix *Uab, const gsl_vector *ab, gsl_matrix *Pab) -{ - size_t index_ab, index_aw, index_bw, index_ww; - double p_ab; - double ps_ab, ps_aw, ps_bw, ps_ww; - - for (size_t p=0; p<=n_cvt+1; ++p) { - for (size_t a=p+1; a<=n_cvt+2; ++a) { - for (size_t b=a; b<=n_cvt+2; ++b) { - index_ab=GetabIndex (a, b, n_cvt); - if (p==0) { - gsl_vector_const_view Uab_col=gsl_matrix_const_column (Uab, index_ab); - gsl_blas_ddot (Hi_eval, &Uab_col.vector, &p_ab); - if (e_mode!=0) {p_ab=gsl_vector_get (ab, index_ab)-p_ab;} - gsl_matrix_set (Pab, 0, index_ab, p_ab); - } - else { - index_aw=GetabIndex (a, p, n_cvt); - index_bw=GetabIndex (b, p, n_cvt); - index_ww=GetabIndex (p, p, n_cvt); - - ps_ab=gsl_matrix_get (Pab, p-1, index_ab); - ps_aw=gsl_matrix_get (Pab, p-1, index_aw); - ps_bw=gsl_matrix_get (Pab, p-1, index_bw); - ps_ww=gsl_matrix_get (Pab, p-1, index_ww); - - p_ab=ps_ab-ps_aw*ps_bw/ps_ww; - gsl_matrix_set (Pab, p, index_ab, p_ab); - } - } - } - } - return; -} - - -void CalcPPab (const size_t n_cvt, const size_t e_mode, const gsl_vector *HiHi_eval, const gsl_matrix *Uab, const gsl_vector *ab, const gsl_matrix *Pab, gsl_matrix *PPab) -{ - size_t index_ab, index_aw, index_bw, index_ww; - double p2_ab; - double ps2_ab, ps_aw, ps_bw, ps_ww, ps2_aw, ps2_bw, ps2_ww; - - for (size_t p=0; p<=n_cvt+1; ++p) { - for (size_t a=p+1; a<=n_cvt+2; ++a) { - for (size_t b=a; b<=n_cvt+2; ++b) { - index_ab=GetabIndex (a, b, n_cvt); - if (p==0) { - gsl_vector_const_view Uab_col=gsl_matrix_const_column (Uab, index_ab); - gsl_blas_ddot (HiHi_eval, &Uab_col.vector, &p2_ab); - if (e_mode!=0) {p2_ab=p2_ab-gsl_vector_get (ab, index_ab)+2.0*gsl_matrix_get (Pab, 0, index_ab);} - gsl_matrix_set (PPab, 0, index_ab, p2_ab); - } - else { - index_aw=GetabIndex (a, p, n_cvt); - index_bw=GetabIndex (b, p, n_cvt); - index_ww=GetabIndex (p, p, n_cvt); - - ps2_ab=gsl_matrix_get (PPab, p-1, index_ab); - ps_aw=gsl_matrix_get (Pab, p-1, index_aw); - ps_bw=gsl_matrix_get (Pab, p-1, index_bw); - ps_ww=gsl_matrix_get (Pab, p-1, index_ww); - ps2_aw=gsl_matrix_get (PPab, p-1, index_aw); - ps2_bw=gsl_matrix_get (PPab, p-1, index_bw); - ps2_ww=gsl_matrix_get (PPab, p-1, index_ww); - - p2_ab=ps2_ab+ps_aw*ps_bw*ps2_ww/(ps_ww*ps_ww); - p2_ab-=(ps_aw*ps2_bw+ps_bw*ps2_aw)/ps_ww; - gsl_matrix_set (PPab, p, index_ab, p2_ab); - - } - } - } - } - return; -} - - -void CalcPPPab (const size_t n_cvt, const size_t e_mode, const gsl_vector *HiHiHi_eval, const gsl_matrix *Uab, const gsl_vector *ab, const gsl_matrix *Pab, const gsl_matrix *PPab, gsl_matrix *PPPab) -{ - size_t index_ab, index_aw, index_bw, index_ww; - double p3_ab; - double ps3_ab, ps_aw, ps_bw, ps_ww, ps2_aw, ps2_bw, ps2_ww, ps3_aw, ps3_bw, ps3_ww; - - for (size_t p=0; p<=n_cvt+1; ++p) { - for (size_t a=p+1; a<=n_cvt+2; ++a) { - for (size_t b=a; b<=n_cvt+2; ++b) { - index_ab=GetabIndex (a, b, n_cvt); - if (p==0) { - gsl_vector_const_view Uab_col=gsl_matrix_const_column (Uab, index_ab); - gsl_blas_ddot (HiHiHi_eval, &Uab_col.vector, &p3_ab); - if (e_mode!=0) {p3_ab=gsl_vector_get (ab, index_ab)-p3_ab+3.0*gsl_matrix_get (PPab, 0, index_ab)-3.0*gsl_matrix_get (Pab, 0, index_ab);} - gsl_matrix_set (PPPab, 0, index_ab, p3_ab); - } - else { - index_aw=GetabIndex (a, p, n_cvt); - index_bw=GetabIndex (b, p, n_cvt); - index_ww=GetabIndex (p, p, n_cvt); - - ps3_ab=gsl_matrix_get (PPPab, p-1, index_ab); - ps_aw=gsl_matrix_get (Pab, p-1, index_aw); - ps_bw=gsl_matrix_get (Pab, p-1, index_bw); - ps_ww=gsl_matrix_get (Pab, p-1, index_ww); - ps2_aw=gsl_matrix_get (PPab, p-1, index_aw); - ps2_bw=gsl_matrix_get (PPab, p-1, index_bw); - ps2_ww=gsl_matrix_get (PPab, p-1, index_ww); - ps3_aw=gsl_matrix_get (PPPab, p-1, index_aw); - ps3_bw=gsl_matrix_get (PPPab, p-1, index_bw); - ps3_ww=gsl_matrix_get (PPPab, p-1, index_ww); - - p3_ab=ps3_ab-ps_aw*ps_bw*ps2_ww*ps2_ww/(ps_ww*ps_ww*ps_ww); - p3_ab-=(ps_aw*ps3_bw+ps_bw*ps3_aw+ps2_aw*ps2_bw)/ps_ww; - p3_ab+=(ps_aw*ps2_bw*ps2_ww+ps_bw*ps2_aw*ps2_ww+ps_aw*ps_bw*ps3_ww)/(ps_ww*ps_ww); - - gsl_matrix_set (PPPab, p, index_ab, p3_ab); - } - } - } - } - return; -} - - - -double LogL_f (double l, void *params) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt;} else {nc_total=n_cvt+1;} - - double f=0.0, logdet_h=0.0, d; - size_t index_yy; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - for (size_t i=0; i<(p->eval)->size; ++i) { - d=gsl_vector_get (v_temp, i); - logdet_h+=log(fabs(d)); - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - - double c=0.5*(double)ni_test*(log((double)ni_test)-log(2*M_PI)-1.0); - - index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, nc_total, index_yy); - f=c-0.5*logdet_h-0.5*(double)ni_test*log(P_yy); - - gsl_matrix_free (Pab); - gsl_vector_free (Hi_eval); - gsl_vector_free (v_temp); - return f; -} - - - - - - -double LogL_dev1 (double l, void *params) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt;} else {nc_total=n_cvt+1;} - - double dev1=0.0, trace_Hi=0.0; - size_t index_yy; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - gsl_vector_memcpy (HiHi_eval, Hi_eval); - gsl_vector_mul (HiHi_eval, Hi_eval); - - gsl_vector_set_all (v_temp, 1.0); - gsl_blas_ddot (Hi_eval, v_temp, &trace_Hi); - - if (p->e_mode!=0) {trace_Hi=(double)ni_test-trace_Hi;} - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - CalcPPab (n_cvt, p->e_mode, HiHi_eval, p->Uab, p->ab, Pab, PPab); - - double trace_HiK=((double)ni_test-trace_Hi)/l; - - index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - - double P_yy=gsl_matrix_get (Pab, nc_total, index_yy); - double PP_yy=gsl_matrix_get (PPab, nc_total, index_yy); - double yPKPy=(P_yy-PP_yy)/l; - dev1=-0.5*trace_HiK+0.5*(double)ni_test*yPKPy/P_yy; - - gsl_matrix_free (Pab); - gsl_matrix_free (PPab); - gsl_vector_free (Hi_eval); - gsl_vector_free (HiHi_eval); - gsl_vector_free (v_temp); - - return dev1; -} - - - - -double LogL_dev2 (double l, void *params) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt;} else {nc_total=n_cvt+1;} - - double dev2=0.0, trace_Hi=0.0, trace_HiHi=0.0; - size_t index_yy; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - gsl_vector_memcpy (HiHi_eval, Hi_eval); - gsl_vector_mul (HiHi_eval, Hi_eval); - gsl_vector_memcpy (HiHiHi_eval, HiHi_eval); - gsl_vector_mul (HiHiHi_eval, Hi_eval); - - gsl_vector_set_all (v_temp, 1.0); - gsl_blas_ddot (Hi_eval, v_temp, &trace_Hi); - gsl_blas_ddot (HiHi_eval, v_temp, &trace_HiHi); - - if (p->e_mode!=0) { - trace_Hi=(double)ni_test-trace_Hi; - trace_HiHi=2*trace_Hi+trace_HiHi-(double)ni_test; - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - CalcPPab (n_cvt, p->e_mode, HiHi_eval, p->Uab, p->ab, Pab, PPab); - CalcPPPab (n_cvt, p->e_mode, HiHiHi_eval, p->Uab, p->ab, Pab, PPab, PPPab); - - double trace_HiKHiK=((double)ni_test+trace_HiHi-2*trace_Hi)/(l*l); - - index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, nc_total, index_yy); - double PP_yy=gsl_matrix_get (PPab, nc_total, index_yy); - double PPP_yy=gsl_matrix_get (PPPab, nc_total, index_yy); - - double yPKPy=(P_yy-PP_yy)/l; - double yPKPKPy=(P_yy+PPP_yy-2.0*PP_yy)/(l*l); - - dev2=0.5*trace_HiKHiK-0.5*(double)ni_test*(2.0*yPKPKPy*P_yy-yPKPy*yPKPy)/(P_yy*P_yy); - - gsl_matrix_free (Pab); - gsl_matrix_free (PPab); - gsl_matrix_free (PPPab); - gsl_vector_free (Hi_eval); - gsl_vector_free (HiHi_eval); - gsl_vector_free (HiHiHi_eval); - gsl_vector_free (v_temp); - - return dev2; -} - - - - - -void LogL_dev12 (double l, void *params, double *dev1, double *dev2) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt;} else {nc_total=n_cvt+1;} - - double trace_Hi=0.0, trace_HiHi=0.0; - size_t index_yy; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - gsl_vector_memcpy (HiHi_eval, Hi_eval); - gsl_vector_mul (HiHi_eval, Hi_eval); - gsl_vector_memcpy (HiHiHi_eval, HiHi_eval); - gsl_vector_mul (HiHiHi_eval, Hi_eval); - - gsl_vector_set_all (v_temp, 1.0); - gsl_blas_ddot (Hi_eval, v_temp, &trace_Hi); - gsl_blas_ddot (HiHi_eval, v_temp, &trace_HiHi); - - if (p->e_mode!=0) { - trace_Hi=(double)ni_test-trace_Hi; - trace_HiHi=2*trace_Hi+trace_HiHi-(double)ni_test; - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - CalcPPab (n_cvt, p->e_mode, HiHi_eval, p->Uab, p->ab, Pab, PPab); - CalcPPPab (n_cvt, p->e_mode, HiHiHi_eval, p->Uab, p->ab, Pab, PPab, PPPab); - - double trace_HiK=((double)ni_test-trace_Hi)/l; - double trace_HiKHiK=((double)ni_test+trace_HiHi-2*trace_Hi)/(l*l); - - index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - - double P_yy=gsl_matrix_get (Pab, nc_total, index_yy); - double PP_yy=gsl_matrix_get (PPab, nc_total, index_yy); - double PPP_yy=gsl_matrix_get (PPPab, nc_total, index_yy); - - double yPKPy=(P_yy-PP_yy)/l; - double yPKPKPy=(P_yy+PPP_yy-2.0*PP_yy)/(l*l); - - *dev1=-0.5*trace_HiK+0.5*(double)ni_test*yPKPy/P_yy; - *dev2=0.5*trace_HiKHiK-0.5*(double)ni_test*(2.0*yPKPKPy*P_yy-yPKPy*yPKPy)/(P_yy*P_yy); - - gsl_matrix_free (Pab); - gsl_matrix_free (PPab); - gsl_matrix_free (PPPab); - gsl_vector_free (Hi_eval); - gsl_vector_free (HiHi_eval); - gsl_vector_free (HiHiHi_eval); - gsl_vector_free (v_temp); - - return; -} - - - -double LogRL_f (double l, void *params) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - double df; - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt; df=(double)ni_test-(double)n_cvt; } - else {nc_total=n_cvt+1; df=(double)ni_test-(double)n_cvt-1.0;} - - double f=0.0, logdet_h=0.0, logdet_hiw=0.0, d; - size_t index_ww; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *Iab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - for (size_t i=0; i<(p->eval)->size; ++i) { - d=gsl_vector_get (v_temp, i); - logdet_h+=log(fabs(d)); - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - gsl_vector_set_all (v_temp, 1.0); - CalcPab (n_cvt, p->e_mode, v_temp, p->Uab, p->ab, Iab); - - //calculate |WHiW|-|WW| - logdet_hiw=0.0; - for (size_t i=0; i<nc_total; ++i) { - index_ww=GetabIndex (i+1, i+1, n_cvt); - d=gsl_matrix_get (Pab, i, index_ww); - logdet_hiw+=log(d); - d=gsl_matrix_get (Iab, i, index_ww); - logdet_hiw-=log(d); - } - index_ww=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, nc_total, index_ww); - - double c=0.5*df*(log(df)-log(2*M_PI)-1.0); - f=c-0.5*logdet_h-0.5*logdet_hiw-0.5*df*log(P_yy); - - gsl_matrix_free (Pab); - gsl_matrix_free (Iab); - gsl_vector_free (Hi_eval); - gsl_vector_free (v_temp); - return f; -} - - - -double LogRL_dev1 (double l, void *params) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - double df; - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt; df=(double)ni_test-(double)n_cvt; } - else {nc_total=n_cvt+1; df=(double)ni_test-(double)n_cvt-1.0;} - - double dev1=0.0, trace_Hi=0.0; - size_t index_ww; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - gsl_vector_memcpy (HiHi_eval, Hi_eval); - gsl_vector_mul (HiHi_eval, Hi_eval); - - gsl_vector_set_all (v_temp, 1.0); - gsl_blas_ddot (Hi_eval, v_temp, &trace_Hi); - - if (p->e_mode!=0) { - trace_Hi=(double)ni_test-trace_Hi; - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - CalcPPab (n_cvt, p->e_mode, HiHi_eval, p->Uab, p->ab, Pab, PPab); - - //calculate tracePK and trace PKPK - double trace_P=trace_Hi; - double ps_ww, ps2_ww; - for (size_t i=0; i<nc_total; ++i) { - index_ww=GetabIndex (i+1, i+1, n_cvt); - ps_ww=gsl_matrix_get (Pab, i, index_ww); - ps2_ww=gsl_matrix_get (PPab, i, index_ww); - trace_P-=ps2_ww/ps_ww; - } - double trace_PK=(df-trace_P)/l; - - //calculate yPKPy, yPKPKPy - index_ww=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, nc_total, index_ww); - double PP_yy=gsl_matrix_get (PPab, nc_total, index_ww); - double yPKPy=(P_yy-PP_yy)/l; - - dev1=-0.5*trace_PK+0.5*df*yPKPy/P_yy; - - gsl_matrix_free (Pab); - gsl_matrix_free (PPab); - gsl_vector_free (Hi_eval); - gsl_vector_free (HiHi_eval); - gsl_vector_free (v_temp); - - return dev1; -} - - - - -double LogRL_dev2 (double l, void *params) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - double df; - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt; df=(double)ni_test-(double)n_cvt; } - else {nc_total=n_cvt+1; df=(double)ni_test-(double)n_cvt-1.0;} - - double dev2=0.0, trace_Hi=0.0, trace_HiHi=0.0; - size_t index_ww; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - gsl_vector_memcpy (HiHi_eval, Hi_eval); - gsl_vector_mul (HiHi_eval, Hi_eval); - gsl_vector_memcpy (HiHiHi_eval, HiHi_eval); - gsl_vector_mul (HiHiHi_eval, Hi_eval); - - gsl_vector_set_all (v_temp, 1.0); - gsl_blas_ddot (Hi_eval, v_temp, &trace_Hi); - gsl_blas_ddot (HiHi_eval, v_temp, &trace_HiHi); - - if (p->e_mode!=0) { - trace_Hi=(double)ni_test-trace_Hi; - trace_HiHi=2*trace_Hi+trace_HiHi-(double)ni_test; - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - CalcPPab (n_cvt, p->e_mode, HiHi_eval, p->Uab, p->ab, Pab, PPab); - CalcPPPab (n_cvt, p->e_mode, HiHiHi_eval, p->Uab, p->ab, Pab, PPab, PPPab); - - //calculate tracePK and trace PKPK - double trace_P=trace_Hi, trace_PP=trace_HiHi; - double ps_ww, ps2_ww, ps3_ww; - for (size_t i=0; i<nc_total; ++i) { - index_ww=GetabIndex (i+1, i+1, n_cvt); - ps_ww=gsl_matrix_get (Pab, i, index_ww); - ps2_ww=gsl_matrix_get (PPab, i, index_ww); - ps3_ww=gsl_matrix_get (PPPab, i, index_ww); - trace_P-=ps2_ww/ps_ww; - trace_PP+=ps2_ww*ps2_ww/(ps_ww*ps_ww)-2.0*ps3_ww/ps_ww; - } - double trace_PKPK=(df+trace_PP-2.0*trace_P)/(l*l); - - //calculate yPKPy, yPKPKPy - index_ww=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, nc_total, index_ww); - double PP_yy=gsl_matrix_get (PPab, nc_total, index_ww); - double PPP_yy=gsl_matrix_get (PPPab, nc_total, index_ww); - double yPKPy=(P_yy-PP_yy)/l; - double yPKPKPy=(P_yy+PPP_yy-2.0*PP_yy)/(l*l); - - dev2=0.5*trace_PKPK-0.5*df*(2.0*yPKPKPy*P_yy-yPKPy*yPKPy)/(P_yy*P_yy); - - gsl_matrix_free (Pab); - gsl_matrix_free (PPab); - gsl_matrix_free (PPPab); - gsl_vector_free (Hi_eval); - gsl_vector_free (HiHi_eval); - gsl_vector_free (HiHiHi_eval); - gsl_vector_free (v_temp); - - return dev2; -} - - - - -void LogRL_dev12 (double l, void *params, double *dev1, double *dev2) -{ - FUNC_PARAM *p=(FUNC_PARAM *) params; - size_t n_cvt=p->n_cvt; - size_t ni_test=p->ni_test; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - double df; - size_t nc_total; - if (p->calc_null==true) {nc_total=n_cvt; df=(double)ni_test-(double)n_cvt; } - else {nc_total=n_cvt+1; df=(double)ni_test-(double)n_cvt-1.0;} - - double trace_Hi=0.0, trace_HiHi=0.0; - size_t index_ww; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_matrix *PPPab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *HiHiHi_eval=gsl_vector_alloc((p->eval)->size); - gsl_vector *v_temp=gsl_vector_alloc((p->eval)->size); - - gsl_vector_memcpy (v_temp, p->eval); - gsl_vector_scale (v_temp, l); - if (p->e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - gsl_vector_memcpy (HiHi_eval, Hi_eval); - gsl_vector_mul (HiHi_eval, Hi_eval); - gsl_vector_memcpy (HiHiHi_eval, HiHi_eval); - gsl_vector_mul (HiHiHi_eval, Hi_eval); - - gsl_vector_set_all (v_temp, 1.0); - gsl_blas_ddot (Hi_eval, v_temp, &trace_Hi); - gsl_blas_ddot (HiHi_eval, v_temp, &trace_HiHi); - - if (p->e_mode!=0) { - trace_Hi=(double)ni_test-trace_Hi; - trace_HiHi=2*trace_Hi+trace_HiHi-(double)ni_test; - } - - CalcPab (n_cvt, p->e_mode, Hi_eval, p->Uab, p->ab, Pab); - CalcPPab (n_cvt, p->e_mode, HiHi_eval, p->Uab, p->ab, Pab, PPab); - CalcPPPab (n_cvt, p->e_mode, HiHiHi_eval, p->Uab, p->ab, Pab, PPab, PPPab); - - //calculate tracePK and trace PKPK - double trace_P=trace_Hi, trace_PP=trace_HiHi; - double ps_ww, ps2_ww, ps3_ww; - for (size_t i=0; i<nc_total; ++i) { - index_ww=GetabIndex (i+1, i+1, n_cvt); - ps_ww=gsl_matrix_get (Pab, i, index_ww); - ps2_ww=gsl_matrix_get (PPab, i, index_ww); - ps3_ww=gsl_matrix_get (PPPab, i, index_ww); - trace_P-=ps2_ww/ps_ww; - trace_PP+=ps2_ww*ps2_ww/(ps_ww*ps_ww)-2.0*ps3_ww/ps_ww; - } - double trace_PK=(df-trace_P)/l; - double trace_PKPK=(df+trace_PP-2.0*trace_P)/(l*l); - - //calculate yPKPy, yPKPKPy - index_ww=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, nc_total, index_ww); - double PP_yy=gsl_matrix_get (PPab, nc_total, index_ww); - double PPP_yy=gsl_matrix_get (PPPab, nc_total, index_ww); - double yPKPy=(P_yy-PP_yy)/l; - double yPKPKPy=(P_yy+PPP_yy-2.0*PP_yy)/(l*l); - - *dev1=-0.5*trace_PK+0.5*df*yPKPy/P_yy; - *dev2=0.5*trace_PKPK-0.5*df*(2.0*yPKPKPy*P_yy-yPKPy*yPKPy)/(P_yy*P_yy); - - gsl_matrix_free (Pab); - gsl_matrix_free (PPab); - gsl_matrix_free (PPPab); - gsl_vector_free (Hi_eval); - gsl_vector_free (HiHi_eval); - gsl_vector_free (HiHiHi_eval); - gsl_vector_free (v_temp); - - return ; -} - - - - - - - - -void LMM::CalcRLWald (const double &l, const FUNC_PARAM ¶ms, double &beta, double &se, double &p_wald) -{ - size_t n_cvt=params.n_cvt; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - int df=(int)ni_test-(int)n_cvt-1; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc(params.eval->size); - gsl_vector *v_temp=gsl_vector_alloc(params.eval->size); - - gsl_vector_memcpy (v_temp, params.eval); - gsl_vector_scale (v_temp, l); - if (params.e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - CalcPab (n_cvt, params.e_mode, Hi_eval, params.Uab, params.ab, Pab); - - size_t index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - size_t index_xx=GetabIndex (n_cvt+1, n_cvt+1, n_cvt); - size_t index_xy=GetabIndex (n_cvt+2, n_cvt+1, n_cvt); - double P_yy=gsl_matrix_get (Pab, n_cvt, index_yy); - double P_xx=gsl_matrix_get (Pab, n_cvt, index_xx); - double P_xy=gsl_matrix_get (Pab, n_cvt, index_xy); - double Px_yy=gsl_matrix_get (Pab, n_cvt+1, index_yy); - - beta=P_xy/P_xx; - double tau=(double)df/Px_yy; - se=sqrt(1.0/(tau*P_xx)); - p_wald=gsl_cdf_fdist_Q ((P_yy-Px_yy)*tau, 1.0, df); -// p_wald=gsl_cdf_chisq_Q ((P_yy-Px_yy)*tau, 1); - - gsl_matrix_free (Pab); - gsl_vector_free (Hi_eval); - gsl_vector_free (v_temp); - return ; -} - - -void LMM::CalcRLScore (const double &l, const FUNC_PARAM ¶ms, double &beta, double &se, double &p_score) -{ - size_t n_cvt=params.n_cvt; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - int df=(int)ni_test-(int)n_cvt-1; - - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc(params.eval->size); - gsl_vector *v_temp=gsl_vector_alloc(params.eval->size); - - gsl_vector_memcpy (v_temp, params.eval); - gsl_vector_scale (v_temp, l); - if (params.e_mode==0) {gsl_vector_set_all (Hi_eval, 1.0);} else {gsl_vector_memcpy (Hi_eval, v_temp);} - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - CalcPab (n_cvt, params.e_mode, Hi_eval, params.Uab, params.ab, Pab); - - size_t index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - size_t index_xx=GetabIndex (n_cvt+1, n_cvt+1, n_cvt); - size_t index_xy=GetabIndex (n_cvt+2, n_cvt+1, n_cvt); - double P_yy=gsl_matrix_get (Pab, n_cvt, index_yy); - double P_xx=gsl_matrix_get (Pab, n_cvt, index_xx); - double P_xy=gsl_matrix_get (Pab, n_cvt, index_xy); - double Px_yy=gsl_matrix_get (Pab, n_cvt+1, index_yy); - - beta=P_xy/P_xx; - double tau=(double)df/Px_yy; - se=sqrt(1.0/(tau*P_xx)); - - p_score=gsl_cdf_fdist_Q ((double)ni_test*P_xy*P_xy/(P_yy*P_xx), 1.0, df); -// p_score=gsl_cdf_chisq_Q ((double)ni_test*P_xy*P_xy/(P_yy*P_xx), 1); - - gsl_matrix_free (Pab); - gsl_vector_free (Hi_eval); - gsl_vector_free (v_temp); - return ; -} - - - - - - - - -void CalcUab (const gsl_matrix *UtW, const gsl_vector *Uty, gsl_matrix *Uab) -{ - size_t index_ab; - size_t n_cvt=UtW->size2; - - gsl_vector *u_a=gsl_vector_alloc (Uty->size); - - for (size_t a=1; a<=n_cvt+2; ++a) { - if (a==n_cvt+1) {continue;} - - if (a==n_cvt+2) {gsl_vector_memcpy (u_a, Uty);} - else { - gsl_vector_const_view UtW_col=gsl_matrix_const_column (UtW, a-1); - gsl_vector_memcpy (u_a, &UtW_col.vector); - } - - for (size_t b=a; b>=1; --b) { - if (b==n_cvt+1) {continue;} - - index_ab=GetabIndex (a, b, n_cvt); - gsl_vector_view Uab_col=gsl_matrix_column (Uab, index_ab); - - if (b==n_cvt+2) {gsl_vector_memcpy (&Uab_col.vector, Uty);} - else { - gsl_vector_const_view UtW_col=gsl_matrix_const_column (UtW, b-1); - gsl_vector_memcpy (&Uab_col.vector, &UtW_col.vector); - } - - gsl_vector_mul(&Uab_col.vector, u_a); - } - } - - gsl_vector_free (u_a); - return; -} - - -void CalcUab (const gsl_matrix *UtW, const gsl_vector *Uty, const gsl_vector *Utx, gsl_matrix *Uab) -{ - size_t index_ab; - size_t n_cvt=UtW->size2; - - for (size_t b=1; b<=n_cvt+2; ++b) { - index_ab=GetabIndex (n_cvt+1, b, n_cvt); - gsl_vector_view Uab_col=gsl_matrix_column (Uab, index_ab); - - if (b==n_cvt+2) {gsl_vector_memcpy (&Uab_col.vector, Uty);} - else if (b==n_cvt+1) {gsl_vector_memcpy (&Uab_col.vector, Utx);} - else { - gsl_vector_const_view UtW_col=gsl_matrix_const_column (UtW, b-1); - gsl_vector_memcpy (&Uab_col.vector, &UtW_col.vector); - } - - gsl_vector_mul(&Uab_col.vector, Utx); - } - - return; -} - - - -void Calcab (const gsl_matrix *W, const gsl_vector *y, gsl_vector *ab) -{ - size_t index_ab; - size_t n_cvt=W->size2; - - double d; - gsl_vector *v_a=gsl_vector_alloc (y->size); - gsl_vector *v_b=gsl_vector_alloc (y->size); - - for (size_t a=1; a<=n_cvt+2; ++a) { - if (a==n_cvt+1) {continue;} - - if (a==n_cvt+2) {gsl_vector_memcpy (v_a, y);} - else { - gsl_vector_const_view W_col=gsl_matrix_const_column (W, a-1); - gsl_vector_memcpy (v_a, &W_col.vector); - } - - for (size_t b=a; b>=1; --b) { - if (b==n_cvt+1) {continue;} - - index_ab=GetabIndex (a, b, n_cvt); - - if (b==n_cvt+2) {gsl_vector_memcpy (v_b, y);} - else { - gsl_vector_const_view W_col=gsl_matrix_const_column (W, b-1); - gsl_vector_memcpy (v_b, &W_col.vector); - } - - gsl_blas_ddot (v_a, v_b, &d); - gsl_vector_set(ab, index_ab, d); - } - } - - gsl_vector_free (v_a); - gsl_vector_free (v_b); - return; -} - - -void Calcab (const gsl_matrix *W, const gsl_vector *y, const gsl_vector *x, gsl_vector *ab) -{ - size_t index_ab; - size_t n_cvt=W->size2; - - double d; - gsl_vector *v_b=gsl_vector_alloc (y->size); - - for (size_t b=1; b<=n_cvt+2; ++b) { - index_ab=GetabIndex (n_cvt+1, b, n_cvt); - - if (b==n_cvt+2) {gsl_vector_memcpy (v_b, y);} - else if (b==n_cvt+1) {gsl_vector_memcpy (v_b, x);} - else { - gsl_vector_const_view W_col=gsl_matrix_const_column (W, b-1); - gsl_vector_memcpy (v_b, &W_col.vector); - } - - gsl_blas_ddot (x, v_b, &d); - gsl_vector_set(ab, index_ab, d); - } - - gsl_vector_free (v_b); - - return; -} - - - - - -void LMM::AnalyzeGene (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Utx, const gsl_matrix *W, const gsl_vector *x) -{ - ifstream infile (file_gene.c_str(), ifstream::in); - if (!infile) {cout<<"error reading gene expression file:"<<file_gene<<endl; return;} - - clock_t time_start=clock(); - - string line; - char *ch_ptr; - - double lambda_mle=0, lambda_remle=0, beta=0, se=0, p_wald=0, p_lrt=0, p_score=0; - double logl_H1=0.0, logl_H0=0.0, l_H0; - int c_phen; - string rs; //gene id - double d; - - //Calculate basic quantities - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - gsl_vector *y=gsl_vector_alloc (U->size1); - gsl_vector *Uty=gsl_vector_alloc (U->size2); - gsl_matrix *Uab=gsl_matrix_alloc (U->size2, n_index); - gsl_vector *ab=gsl_vector_alloc (n_index); - - //header - getline(infile, line); - - for (size_t t=0; t<ng_total; t++) { - !safeGetline(infile, line).eof(); - if (t%d_pace==0 || t==ng_total-1) {ProgressBar ("Performing Analysis ", t, ng_total-1);} - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - rs=ch_ptr; - - c_phen=0; - for (size_t i=0; i<indicator_idv.size(); ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==0) {continue;} - - d=atof(ch_ptr); - gsl_vector_set(y, c_phen, d); - - c_phen++; - } - - time_start=clock(); - gsl_blas_dgemv (CblasTrans, 1.0, U, y, 0.0, Uty); - time_UtX+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //calculate null - time_start=clock(); - - gsl_matrix_set_zero (Uab); - - CalcUab (UtW, Uty, Uab); - FUNC_PARAM param0={false, ni_test, n_cvt, eval, Uab, ab, 0}; - - if (a_mode==2 || a_mode==3 || a_mode==4) { - CalcLambda('L', param0, l_min, l_max, n_region, l_H0, logl_H0); - } - - //calculate alternative - CalcUab(UtW, Uty, Utx, Uab); - FUNC_PARAM param1={false, ni_test, n_cvt, eval, Uab, ab, 0}; - - //3 is before 1 - if (a_mode==3 || a_mode==4) { - CalcRLScore (l_H0, param1, beta, se, p_score); - } - - if (a_mode==1 || a_mode==4) { - CalcLambda ('R', param1, l_min, l_max, n_region, lambda_remle, logl_H1); - CalcRLWald (lambda_remle, param1, beta, se, p_wald); - } - - if (a_mode==2 || a_mode==4) { - CalcLambda ('L', param1, l_min, l_max, n_region, lambda_mle, logl_H1); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_H0), 1); - } - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - SUMSTAT SNPs={beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score}; - sumStat.push_back(SNPs); - } - cout<<endl; - - gsl_vector_free (y); - gsl_vector_free (Uty); - gsl_matrix_free (Uab); - gsl_vector_free (ab); - - infile.close(); - infile.clear(); - - return; -} - - - - - -void LMM::AnalyzeBimbam (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const gsl_matrix *W, const gsl_vector *y) -{ - igzstream infile (file_geno.c_str(), igzstream::in); -// ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return;} - - clock_t time_start=clock(); - - string line; - char *ch_ptr; - - double lambda_mle=0, lambda_remle=0, beta=0, se=0, p_wald=0, p_lrt=0, p_score=0; - double logl_H1=0.0; - int n_miss, c_phen; - double geno, x_mean; - - //Calculate basic quantities - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - gsl_vector *x=gsl_vector_alloc (U->size1); - gsl_vector *x_miss=gsl_vector_alloc (U->size1); - gsl_vector *Utx=gsl_vector_alloc (U->size2); - gsl_matrix *Uab=gsl_matrix_alloc (U->size2, n_index); - gsl_vector *ab=gsl_vector_alloc (n_index); - - gsl_matrix_set_zero (Uab); - CalcUab (UtW, Uty, Uab); -// if (e_mode!=0) { -// gsl_vector_set_zero (ab); -// Calcab (W, y, ab); -// } - - //start reading genotypes and analyze - for (size_t t=0; t<indicator_snp.size(); ++t) { -// if (t>1) {break;} - !safeGetline(infile, line).eof(); - if (t%d_pace==0 || t==(ns_total-1)) {ProgressBar ("Reading SNPs ", t, ns_total-1);} - if (indicator_snp[t]==0) {continue;} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - ch_ptr=strtok (NULL, " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - x_mean=0.0; c_phen=0; n_miss=0; - gsl_vector_set_zero(x_miss); - for (size_t i=0; i<ni_total; ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==0) {continue;} - - if (strcmp(ch_ptr, "NA")==0) {gsl_vector_set(x_miss, c_phen, 0.0); n_miss++;} - else { - geno=atof(ch_ptr); - - gsl_vector_set(x, c_phen, geno); - gsl_vector_set(x_miss, c_phen, 1.0); - x_mean+=geno; - } - c_phen++; - } - - x_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<ni_test; ++i) { - if (gsl_vector_get (x_miss, i)==0) {gsl_vector_set(x, i, x_mean);} - geno=gsl_vector_get(x, i); - if (x_mean>1) { - gsl_vector_set(x, i, 2-geno); - } - } - - - //calculate statistics - time_start=clock(); - gsl_blas_dgemv (CblasTrans, 1.0, U, x, 0.0, Utx); - time_UtX+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - CalcUab(UtW, Uty, Utx, Uab); -// if (e_mode!=0) { -// Calcab (W, y, x, ab); -// } - - time_start=clock(); - FUNC_PARAM param1={false, ni_test, n_cvt, eval, Uab, ab, 0}; - - //3 is before 1 - if (a_mode==3 || a_mode==4) { - CalcRLScore (l_mle_null, param1, beta, se, p_score); - } - - if (a_mode==1 || a_mode==4) { - CalcLambda ('R', param1, l_min, l_max, n_region, lambda_remle, logl_H1); - CalcRLWald (lambda_remle, param1, beta, se, p_wald); - } - - if (a_mode==2 || a_mode==4) { - CalcLambda ('L', param1, l_min, l_max, n_region, lambda_mle, logl_H1); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_mle_H0), 1); - } - - if (x_mean>1) {beta*=-1;} - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - SUMSTAT SNPs={beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score}; - sumStat.push_back(SNPs); - } - cout<<endl; - - gsl_vector_free (x); - gsl_vector_free (x_miss); - gsl_vector_free (Utx); - gsl_matrix_free (Uab); - gsl_vector_free (ab); - - infile.close(); - infile.clear(); - - return; -} - - - - - - - -void LMM::AnalyzePlink (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const gsl_matrix *W, const gsl_vector *y) -{ - string file_bed=file_bfile+".bed"; - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return;} - - clock_t time_start=clock(); - - char ch[1]; - bitset<8> b; - - double lambda_mle=0, lambda_remle=0, beta=0, se=0, p_wald=0, p_lrt=0, p_score=0; - double logl_H1=0.0; - int n_bit, n_miss, ci_total, ci_test; - double geno, x_mean; - - //Calculate basic quantities - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - gsl_vector *x=gsl_vector_alloc (U->size1); - gsl_vector *Utx=gsl_vector_alloc (U->size2); - gsl_matrix *Uab=gsl_matrix_alloc (U->size2, n_index); - gsl_vector *ab=gsl_vector_alloc (n_index); - - gsl_matrix_set_zero (Uab); - CalcUab (UtW, Uty, Uab); -// if (e_mode!=0) { -// gsl_vector_set_zero (ab); -// Calcab (W, y, ab); -// } - - //calculate n_bit and c, the number of bit for each snp - if (ni_total%4==0) {n_bit=ni_total/4;} - else {n_bit=ni_total/4+1; } - - //print the first three majic numbers - for (int i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - - for (vector<SNPINFO>::size_type t=0; t<snpInfo.size(); ++t) { - if (t%d_pace==0 || t==snpInfo.size()-1) {ProgressBar ("Reading SNPs ", t, snpInfo.size()-1);} - if (indicator_snp[t]==0) {continue;} - - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - //read genotypes - x_mean=0.0; n_miss=0; ci_total=0; ci_test=0; - for (int i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && ci_total==(int)ni_total) {break;} - if (indicator_idv[ci_total]==0) {ci_total++; continue;} - - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(x, ci_test, 2); x_mean+=2.0; } - else {gsl_vector_set(x, ci_test, 1); x_mean+=1.0; } - } - else { - if (b[2*j+1]==1) {gsl_vector_set(x, ci_test, 0); } - else {gsl_vector_set(x, ci_test, -9); n_miss++; } - } - - ci_total++; - ci_test++; - } - } - - x_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<ni_test; ++i) { - geno=gsl_vector_get(x,i); - if (geno==-9) {gsl_vector_set(x, i, x_mean); geno=x_mean;} - if (x_mean>1) { - gsl_vector_set(x, i, 2-geno); - } - } - - //calculate statistics - time_start=clock(); - gsl_blas_dgemv (CblasTrans, 1.0, U, x, 0.0, Utx); - time_UtX+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - CalcUab(UtW, Uty, Utx, Uab); -// if (e_mode!=0) { -// Calcab (W, y, x, ab); -// } - - time_start=clock(); - FUNC_PARAM param1={false, ni_test, n_cvt, eval, Uab, ab, 0}; - - //3 is before 1, for beta - if (a_mode==3 || a_mode==4) { - CalcRLScore (l_mle_null, param1, beta, se, p_score); - } - - if (a_mode==1 || a_mode==4) { - CalcLambda ('R', param1, l_min, l_max, n_region, lambda_remle, logl_H1); - CalcRLWald (lambda_remle, param1, beta, se, p_wald); - } - - if (a_mode==2 || a_mode==4) { - CalcLambda ('L', param1, l_min, l_max, n_region, lambda_mle, logl_H1); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_mle_H0), 1); - } - - if (x_mean>1) {beta*=-1;} - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - SUMSTAT SNPs={beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score}; - sumStat.push_back(SNPs); - } - cout<<endl; - - gsl_vector_free (x); - gsl_vector_free (Utx); - gsl_matrix_free (Uab); - gsl_vector_free (ab); - - infile.close(); - infile.clear(); - - return; -} - - - - - -void MatrixCalcLR (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, const double l_min, const double l_max, const size_t n_region, vector<pair<size_t, double> > &pos_loglr) -{ - double logl_H0, logl_H1, log_lr, lambda0, lambda1; - - gsl_vector *w=gsl_vector_alloc (Uty->size); - gsl_matrix *Utw=gsl_matrix_alloc (Uty->size, 1); - gsl_matrix *Uab=gsl_matrix_alloc (Uty->size, 6); - gsl_vector *ab=gsl_vector_alloc (6); - - gsl_vector_set_zero(ab); - gsl_vector_set_all (w, 1.0); - gsl_vector_view Utw_col=gsl_matrix_column (Utw, 0); - gsl_blas_dgemv (CblasTrans, 1.0, U, w, 0.0, &Utw_col.vector); - - CalcUab (Utw, Uty, Uab) ; - FUNC_PARAM param0={true, Uty->size, 1, K_eval, Uab, ab, 0}; - - CalcLambda('L', param0, l_min, l_max, n_region, lambda0, logl_H0); - - for (size_t i=0; i<UtX->size2; ++i) { - gsl_vector_const_view UtX_col=gsl_matrix_const_column (UtX, i); - CalcUab(Utw, Uty, &UtX_col.vector, Uab); - FUNC_PARAM param1={false, UtX->size1, 1, K_eval, Uab, ab, 0}; - - CalcLambda ('L', param1, l_min, l_max, n_region, lambda1, logl_H1); - log_lr=logl_H1-logl_H0; - - pos_loglr.push_back(make_pair(i,log_lr) ); - } - - gsl_vector_free (w); - gsl_matrix_free (Utw); - gsl_matrix_free (Uab); - gsl_vector_free (ab); - - return; -} - - - - -void CalcLambda (const char func_name, FUNC_PARAM ¶ms, const double l_min, const double l_max, const size_t n_region, double &lambda, double &logf) -{ - if (func_name!='R' && func_name!='L' && func_name!='r' && func_name!='l') {cout<<"func_name only takes 'R' or 'L': 'R' for log-restricted likelihood, 'L' for log-likelihood."<<endl; return;} - - vector<pair<double, double> > lambda_lh; - - //evaluate first order derivates in different intervals - double lambda_l, lambda_h, lambda_interval=log(l_max/l_min)/(double)n_region; - double dev1_l, dev1_h, logf_l, logf_h; - - for (size_t i=0; i<n_region; ++i) { - lambda_l=l_min*exp(lambda_interval*i); - lambda_h=l_min*exp(lambda_interval*(i+1.0)); - - if (func_name=='R' || func_name=='r') { - dev1_l=LogRL_dev1 (lambda_l, ¶ms); - dev1_h=LogRL_dev1 (lambda_h, ¶ms); - } - else { - dev1_l=LogL_dev1 (lambda_l, ¶ms); - dev1_h=LogL_dev1 (lambda_h, ¶ms); - } - - if (dev1_l*dev1_h<=0) { - lambda_lh.push_back(make_pair(lambda_l, lambda_h)); - } - } - - //if derivates do not change signs in any interval - if (lambda_lh.empty()) { - if (func_name=='R' || func_name=='r') { - logf_l=LogRL_f (l_min, ¶ms); - logf_h=LogRL_f (l_max, ¶ms); - } - else { - logf_l=LogL_f (l_min, ¶ms); - logf_h=LogL_f (l_max, ¶ms); - } - - if (logf_l>=logf_h) {lambda=l_min; logf=logf_l;} else {lambda=l_max; logf=logf_h;} - } - else { - //if derivates change signs - int status; - int iter=0, max_iter=100; - double l, l_temp; - - gsl_function F; - gsl_function_fdf FDF; - - F.params=¶ms; - FDF.params=¶ms; - - if (func_name=='R' || func_name=='r') { - F.function=&LogRL_dev1; - FDF.f=&LogRL_dev1; - FDF.df=&LogRL_dev2; - FDF.fdf=&LogRL_dev12; - } - else { - F.function=&LogL_dev1; - FDF.f=&LogL_dev1; - FDF.df=&LogL_dev2; - FDF.fdf=&LogL_dev12; - } - - const gsl_root_fsolver_type *T_f; - gsl_root_fsolver *s_f; - T_f=gsl_root_fsolver_brent; - s_f=gsl_root_fsolver_alloc (T_f); - - const gsl_root_fdfsolver_type *T_fdf; - gsl_root_fdfsolver *s_fdf; - T_fdf=gsl_root_fdfsolver_newton; - s_fdf=gsl_root_fdfsolver_alloc(T_fdf); - - for (vector<double>::size_type i=0; i<lambda_lh.size(); ++i) { - lambda_l=lambda_lh[i].first; lambda_h=lambda_lh[i].second; - - gsl_root_fsolver_set (s_f, &F, lambda_l, lambda_h); - - do { - iter++; - status=gsl_root_fsolver_iterate (s_f); - l=gsl_root_fsolver_root (s_f); - lambda_l=gsl_root_fsolver_x_lower (s_f); - lambda_h=gsl_root_fsolver_x_upper (s_f); - status=gsl_root_test_interval (lambda_l, lambda_h, 0, 1e-1); - } - while (status==GSL_CONTINUE && iter<max_iter); - - iter=0; - - gsl_root_fdfsolver_set (s_fdf, &FDF, l); - - do { - iter++; - status=gsl_root_fdfsolver_iterate (s_fdf); - l_temp=l; - l=gsl_root_fdfsolver_root (s_fdf); - status=gsl_root_test_delta (l, l_temp, 0, 1e-5); - } - while (status==GSL_CONTINUE && iter<max_iter && l>l_min && l<l_max); - - l=l_temp; - if (l<l_min) {l=l_min;} - if (l>l_max) {l=l_max;} - if (func_name=='R' || func_name=='r') {logf_l=LogRL_f (l, ¶ms);} else {logf_l=LogL_f (l, ¶ms);} - - if (i==0) {logf=logf_l; lambda=l;} - else if (logf<logf_l) {logf=logf_l; lambda=l;} - else {} - } - gsl_root_fsolver_free (s_f); - gsl_root_fdfsolver_free (s_fdf); - - if (func_name=='R' || func_name=='r') { - logf_l=LogRL_f (l_min, ¶ms); - logf_h=LogRL_f (l_max, ¶ms); - } - else { - logf_l=LogL_f (l_min, ¶ms); - logf_h=LogL_f (l_max, ¶ms); - } - - if (logf_l>logf) {lambda=l_min; logf=logf_l;} - if (logf_h>logf) {lambda=l_max; logf=logf_h;} - } - - return; -} - - - - - -//calculate lambda in the null model -void CalcLambda (const char func_name, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const double l_min, const double l_max, const size_t n_region, double &lambda, double &logl_H0) -{ - if (func_name!='R' && func_name!='L' && func_name!='r' && func_name!='l') {cout<<"func_name only takes 'R' or 'L': 'R' for log-restricted likelihood, 'L' for log-likelihood."<<endl; return;} - - size_t n_cvt=UtW->size2, ni_test=UtW->size1; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - gsl_matrix *Uab=gsl_matrix_alloc (ni_test, n_index); - gsl_vector *ab=gsl_vector_alloc (n_index); - - gsl_matrix_set_zero (Uab); - CalcUab (UtW, Uty, Uab); -// if (e_mode!=0) { -// gsl_vector_set_zero (ab); -// Calcab (W, y, ab); -// } - - FUNC_PARAM param0={true, ni_test, n_cvt, eval, Uab, ab, 0}; - - CalcLambda(func_name, param0, l_min, l_max, n_region, lambda, logl_H0); - - gsl_matrix_free(Uab); - gsl_vector_free(ab); - - return; -} - - -//obtain REMLE estimate for PVE using lambda_remle -void CalcPve (const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const double lambda, const double trace_G, double &pve, double &pve_se) -{ - size_t n_cvt=UtW->size2, ni_test=UtW->size1; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - gsl_matrix *Uab=gsl_matrix_alloc (ni_test, n_index); - gsl_vector *ab=gsl_vector_alloc (n_index); - - gsl_matrix_set_zero (Uab); - CalcUab (UtW, Uty, Uab); - // if (e_mode!=0) { - // gsl_vector_set_zero (ab); - // Calcab (W, y, ab); - // } - - FUNC_PARAM param0={true, ni_test, n_cvt, eval, Uab, ab, 0}; - - double se=sqrt(-1.0/LogRL_dev2 (lambda, ¶m0)); - - pve=trace_G*lambda/(trace_G*lambda+1.0); - pve_se=trace_G/((trace_G*lambda+1.0)*(trace_G*lambda+1.0))*se; - - gsl_matrix_free (Uab); - gsl_vector_free (ab); - return; -} - -//obtain REML estimate for Vg and Ve using lambda_remle -//obtain beta and se(beta) for coefficients -//ab is not used when e_mode==0 -void CalcLmmVgVeBeta (const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const double lambda, double &vg, double &ve, gsl_vector *beta, gsl_vector *se_beta) -{ - size_t n_cvt=UtW->size2, ni_test=UtW->size1; - size_t n_index=(n_cvt+2+1)*(n_cvt+2)/2; - - gsl_matrix *Uab=gsl_matrix_alloc (ni_test, n_index); - gsl_vector *ab=gsl_vector_alloc (n_index); - gsl_matrix *Pab=gsl_matrix_alloc (n_cvt+2, n_index); - gsl_vector *Hi_eval=gsl_vector_alloc(eval->size); - gsl_vector *v_temp=gsl_vector_alloc(eval->size); - gsl_matrix *HiW=gsl_matrix_alloc(eval->size, UtW->size2); - gsl_matrix *WHiW=gsl_matrix_alloc(UtW->size2, UtW->size2); - gsl_vector *WHiy=gsl_vector_alloc(UtW->size2); - gsl_matrix *Vbeta=gsl_matrix_alloc(UtW->size2, UtW->size2); - - gsl_matrix_set_zero (Uab); - CalcUab (UtW, Uty, Uab); - - gsl_vector_memcpy (v_temp, eval); - gsl_vector_scale (v_temp, lambda); - gsl_vector_set_all (Hi_eval, 1.0); - gsl_vector_add_constant (v_temp, 1.0); - gsl_vector_div (Hi_eval, v_temp); - - //calculate beta - gsl_matrix_memcpy (HiW, UtW); - for (size_t i=0; i<UtW->size2; i++) { - gsl_vector_view HiW_col=gsl_matrix_column(HiW, i); - gsl_vector_mul(&HiW_col.vector, Hi_eval); - } - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, HiW, UtW, 0.0, WHiW); - gsl_blas_dgemv (CblasTrans, 1.0, HiW, Uty, 0.0, WHiy); - - int sig; - gsl_permutation * pmt=gsl_permutation_alloc (UtW->size2); - LUDecomp (WHiW, pmt, &sig); - LUSolve (WHiW, pmt, WHiy, beta); - LUInvert (WHiW, pmt, Vbeta); - - //calculate vg and ve - CalcPab (n_cvt, 0, Hi_eval, Uab, ab, Pab); - - size_t index_yy=GetabIndex (n_cvt+2, n_cvt+2, n_cvt); - double P_yy=gsl_matrix_get (Pab, n_cvt, index_yy); - - ve=P_yy/(double)(ni_test-n_cvt); - vg=ve*lambda; - - //with ve, calculate se(beta) - gsl_matrix_scale(Vbeta, ve); - - //obtain se_beta - for (size_t i=0; i<Vbeta->size1; i++) { - gsl_vector_set (se_beta, i, sqrt(gsl_matrix_get(Vbeta, i, i) ) ); - } - - gsl_matrix_free(Uab); - gsl_matrix_free(Pab); - gsl_vector_free(ab); - gsl_vector_free(Hi_eval); - gsl_vector_free(v_temp); - gsl_matrix_free(HiW); - gsl_matrix_free(WHiW); - gsl_vector_free(WHiy); - gsl_matrix_free(Vbeta); - - gsl_permutation_free(pmt); - return; -} - diff --git a/lmm.h b/lmm.h deleted file mode 100644 index 45f9b72..0000000 --- a/lmm.h +++ /dev/null @@ -1,111 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __LMM_H__ -#define __LMM_H__ - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - - -#ifdef FORCE_FLOAT -#include "param_float.h" -#include "io_float.h" -#else -#include "param.h" -#include "io.h" -#endif - -using namespace std; - - - -class FUNC_PARAM -{ - -public: - bool calc_null; - size_t ni_test; - size_t n_cvt; - const gsl_vector *eval; - const gsl_matrix *Uab; - const gsl_vector *ab; - size_t e_mode; -}; - - - - -class LMM { - -public: - // IO related parameters - int a_mode; //analysis mode, 1/2/3/4 for Frequentist tests - size_t d_pace; //display pace - - string file_bfile; - string file_geno; - string file_out; - string path_out; - - string file_gene; - - // LMM related parameters - double l_min; - double l_max; - size_t n_region; - double l_mle_null; - double logl_mle_H0; - - // Summary statistics - size_t ni_total, ni_test; //number of individuals - size_t ns_total, ns_test; //number of snps - size_t ng_total, ng_test; //number of genes - size_t n_cvt; - double time_UtX; //time spent on optimization iterations - double time_opt; //time spent on optimization iterations - - vector<int> indicator_idv; //indicator for individuals (phenotypes), 0 missing, 1 available for analysis - vector<int> indicator_snp; //sequence indicator for SNPs: 0 ignored because of (a) maf, (b) miss, (c) non-poly; 1 available for analysis - - vector<SNPINFO> snpInfo; //record SNP information - - // Not included in PARAM - vector<SUMSTAT> sumStat; //Output SNPSummary Data - - // Main functions - void CopyFromParam (PARAM &cPar); - void CopyToParam (PARAM &cPar); - void AnalyzeGene (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Utx, const gsl_matrix *W, const gsl_vector *x); - void AnalyzePlink (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const gsl_matrix *W, const gsl_vector *y); - void AnalyzeBimbam (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const gsl_matrix *W, const gsl_vector *y); - void WriteFiles (); - - void CalcRLWald (const double &lambda, const FUNC_PARAM ¶ms, double &beta, double &se, double &p_wald); - void CalcRLScore (const double &l, const FUNC_PARAM ¶ms, double &beta, double &se, double &p_score); -}; - -void MatrixCalcLR (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, const double l_min, const double l_max, const size_t n_region, vector<pair<size_t, double> > &pos_loglr); -void CalcLambda (const char func_name, FUNC_PARAM ¶ms, const double l_min, const double l_max, const size_t n_region, double &lambda, double &logf); -void CalcLambda (const char func_name, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const double l_min, const double l_max, const size_t n_region, double &lambda, double &logl_H0); -void CalcPve (const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const double lambda, const double trace_G, double &pve, double &pve_se); -void CalcLmmVgVeBeta (const gsl_vector *eval, const gsl_matrix *UtW, const gsl_vector *Uty, const double lambda, double &vg, double &ve, gsl_vector *beta, gsl_vector *se_beta); - -#endif - - diff --git a/main.cpp b/main.cpp deleted file mode 100644 index e1fb336..0000000 --- a/main.cpp +++ /dev/null @@ -1,86 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#include <iostream> -#include <fstream> -#include <sstream> -#include <sys/stat.h> -#include <sys/types.h> - -#include "param.h" - -#ifdef FORCE_FLOAT -#include "gemma_float.h" -#else -#include "gemma.h" -#endif - -using namespace std; - - - -int main(int argc, char * argv[]) -{ - GEMMA cGemma; - PARAM cPar; - - if (argc <= 1) { - cGemma.PrintHeader(); - return EXIT_SUCCESS; - } - if (argc==2 && argv[1][0] == '-' && argv[1][1] == 'h') { - cGemma.PrintHelp(0); - return EXIT_SUCCESS; - } - if (argc==3 && argv[1][0] == '-' && argv[1][1] == 'h') { - string str; - str.assign(argv[2]); - cGemma.PrintHelp(atoi(str.c_str())); - return EXIT_SUCCESS; - } - if (argc==2 && argv[1][0] == '-' && argv[1][1] == 'l') { - cGemma.PrintLicense(); - return EXIT_SUCCESS; - } - - cGemma.Assign(argc, argv, cPar); - - ifstream check_dir((cPar.path_out).c_str()); - if (!check_dir) { - mkdir((cPar.path_out).c_str(), S_IRWXU|S_IRGRP|S_IROTH); - } - - if (cPar.error==true) {return EXIT_FAILURE;} - - if (cPar.mode_silence) {stringstream ss; cout.rdbuf (ss.rdbuf());} - - cPar.CheckParam(); - - if (cPar.error==true) {return EXIT_FAILURE;} - - cGemma.BatchRun(cPar); - - if (cPar.error==true) {return EXIT_FAILURE;} - - cGemma.WriteLog(argc, argv, cPar); - - return EXIT_SUCCESS; -} - - - diff --git a/mathfunc.cpp b/mathfunc.cpp deleted file mode 100644 index 09e58dc..0000000 --- a/mathfunc.cpp +++ /dev/null @@ -1,310 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - - -#include <iostream> -#include <fstream> -#include <sstream> -#include <string> -#include <iomanip> -#include <bitset> -#include <vector> -#include <map> -#include <set> -#include <cstring> -#include <cmath> -#include <stdio.h> -#include <stdlib.h> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" -#include "gsl/gsl_cdf.h" - -#ifdef FORCE_FLOAT -#include "mathfunc_float.h" -#else -#include "mathfunc.h" -#endif - - -using namespace std; - - - -//calculate variance of a vector -double VectorVar (const gsl_vector *v) -{ - double d, m=0.0, m2=0.0; - for (size_t i=0; i<v->size; ++i) { - d=gsl_vector_get (v, i); - m+=d; - m2+=d*d; - } - m/=(double)v->size; - m2/=(double)v->size; - return m2-m*m; -} - - - -//center the matrix G -void CenterMatrix (gsl_matrix *G) -{ - double d; - gsl_vector *w=gsl_vector_alloc (G->size1); - gsl_vector *Gw=gsl_vector_alloc (G->size1); - gsl_vector_set_all (w, 1.0); - - gsl_blas_dgemv (CblasNoTrans, 1.0, G, w, 0.0, Gw); - gsl_blas_dsyr2 (CblasUpper, -1.0/(double)G->size1, Gw, w, G); - gsl_blas_ddot (w, Gw, &d); - gsl_blas_dsyr (CblasUpper, d/((double)G->size1*(double)G->size1), w, G); - - for (size_t i=0; i<G->size1; ++i) { - for (size_t j=0; j<i; ++j) { - d=gsl_matrix_get (G, j, i); - gsl_matrix_set (G, i, j, d); - } - } - - gsl_vector_free(w); - gsl_vector_free(Gw); - - return; -} - - -//center the matrix G -void CenterMatrix (gsl_matrix *G, gsl_vector *w) -{ - double d, wtw; - gsl_vector *Gw=gsl_vector_alloc (G->size1); - - gsl_blas_ddot (w, w, &wtw); - gsl_blas_dgemv (CblasNoTrans, 1.0, G, w, 0.0, Gw); - gsl_blas_dsyr2 (CblasUpper, -1.0/wtw, Gw, w, G); - gsl_blas_ddot (w, Gw, &d); - gsl_blas_dsyr (CblasUpper, d/(wtw*wtw), w, G); - - for (size_t i=0; i<G->size1; ++i) { - for (size_t j=0; j<i; ++j) { - d=gsl_matrix_get (G, j, i); - gsl_matrix_set (G, i, j, d); - } - } - - gsl_vector_free(Gw); - - return; -} - - -//scale the matrix G such that the mean diagonal = 1 -void ScaleMatrix (gsl_matrix *G) -{ - double d=0.0; - - for (size_t i=0; i<G->size1; ++i) { - d+=gsl_matrix_get(G, i, i); - } - d/=(double)G->size1; - - gsl_matrix_scale (G, 1.0/d); - - return; -} - - -//center the vector y -double CenterVector (gsl_vector *y) -{ - double d=0.0; - - for (size_t i=0; i<y->size; ++i) { - d+=gsl_vector_get (y, i); - } - d/=(double)y->size; - - gsl_vector_add_constant (y, -1.0*d); - - return d; -} - - -//calculate UtX -void CalcUtX (const gsl_matrix *U, gsl_matrix *UtX) -{ - gsl_vector *Utx_vec=gsl_vector_alloc (UtX->size1); - for (size_t i=0; i<UtX->size2; ++i) { - gsl_vector_view UtX_col=gsl_matrix_column (UtX, i); - gsl_blas_dgemv (CblasTrans, 1.0, U, &UtX_col.vector, 0.0, Utx_vec); - gsl_vector_memcpy (&UtX_col.vector, Utx_vec); - } - gsl_vector_free (Utx_vec); - return; -} - - -void CalcUtX (const gsl_matrix *U, const gsl_matrix *X, gsl_matrix *UtX) -{ - for (size_t i=0; i<X->size2; ++i) { - gsl_vector_const_view X_col=gsl_matrix_const_column (X, i); - gsl_vector_view UtX_col=gsl_matrix_column (UtX, i); - gsl_blas_dgemv (CblasTrans, 1.0, U, &X_col.vector, 0.0, &UtX_col.vector); - } - return; -} - -void CalcUtX (const gsl_matrix *U, const gsl_vector *x, gsl_vector *Utx) -{ - gsl_blas_dgemv (CblasTrans, 1.0, U, x, 0.0, Utx); - return; -} - - -//Kronecker product -void Kronecker(const gsl_matrix *K, const gsl_matrix *V, gsl_matrix *H) -{ - for (size_t i=0; i<K->size1; i++) { - for (size_t j=0; j<K->size2; j++) { - gsl_matrix_view H_sub=gsl_matrix_submatrix (H, i*V->size1, j*V->size2, V->size1, V->size2); - gsl_matrix_memcpy (&H_sub.matrix, V); - gsl_matrix_scale (&H_sub.matrix, gsl_matrix_get (K, i, j)); - } - } - return; -} - -//symmetric K matrix -void KroneckerSym(const gsl_matrix *K, const gsl_matrix *V, gsl_matrix *H) -{ - for (size_t i=0; i<K->size1; i++) { - for (size_t j=i; j<K->size2; j++) { - gsl_matrix_view H_sub=gsl_matrix_submatrix (H, i*V->size1, j*V->size2, V->size1, V->size2); - gsl_matrix_memcpy (&H_sub.matrix, V); - gsl_matrix_scale (&H_sub.matrix, gsl_matrix_get (K, i, j)); - - if (i!=j) { - gsl_matrix_view H_sub_sym=gsl_matrix_submatrix (H, j*V->size1, i*V->size2, V->size1, V->size2); - gsl_matrix_memcpy (&H_sub_sym.matrix, &H_sub.matrix); - } - } - } - return; -} - - -// this function calculates HWE p value with methods described in Wigginton et al., 2005 AJHG; -// it is based on the code in plink 1.07 -double CalcHWE (const size_t n_hom1, const size_t n_hom2, const size_t n_ab) -{ - if ( (n_hom1+n_hom2+n_ab)==0 ) {return 1;} - - //aa is the rare allele - int n_aa=n_hom1 < n_hom2 ? n_hom1 : n_hom2; - int n_bb=n_hom1 < n_hom2 ? n_hom2 : n_hom1; - - int rare_copies = 2 * n_aa + n_ab; - int genotypes = n_ab + n_bb + n_aa; - - double * het_probs = (double *) malloc( (rare_copies + 1) * sizeof(double)); - if (het_probs == NULL) - cout<<"Internal error: SNP-HWE: Unable to allocate array"<<endl; - - int i; - for (i = 0; i <= rare_copies; i++) - het_probs[i] = 0.0; - - /* start at midpoint */ - int mid = rare_copies * (2 * genotypes - rare_copies) / (2 * genotypes); - - /* check to ensure that midpoint and rare alleles have same parity */ - if ((rare_copies & 1) ^ (mid & 1)) - mid++; - - int curr_hets = mid; - int curr_homr = (rare_copies - mid) / 2; - int curr_homc = genotypes - curr_hets - curr_homr; - - het_probs[mid] = 1.0; - double sum = het_probs[mid]; - for (curr_hets = mid; curr_hets > 1; curr_hets -= 2) - { - het_probs[curr_hets - 2] = het_probs[curr_hets] * curr_hets * (curr_hets - 1.0) - / (4.0 * (curr_homr + 1.0) * (curr_homc + 1.0)); - sum += het_probs[curr_hets - 2]; - - /* 2 fewer heterozygotes for next iteration -> add one rare, one common homozygote */ - curr_homr++; - curr_homc++; - } - - curr_hets = mid; - curr_homr = (rare_copies - mid) / 2; - curr_homc = genotypes - curr_hets - curr_homr; - for (curr_hets = mid; curr_hets <= rare_copies - 2; curr_hets += 2) - { - het_probs[curr_hets + 2] = het_probs[curr_hets] * 4.0 * curr_homr * curr_homc - /((curr_hets + 2.0) * (curr_hets + 1.0)); - sum += het_probs[curr_hets + 2]; - - /* add 2 heterozygotes for next iteration -> subtract one rare, one common homozygote */ - curr_homr--; - curr_homc--; - } - - for (i = 0; i <= rare_copies; i++) - het_probs[i] /= sum; - - /* alternate p-value calculation for p_hi/p_lo - double p_hi = het_probs[n_ab]; - for (i = n_ab + 1; i <= rare_copies; i++) - p_hi += het_probs[i]; - - double p_lo = het_probs[n_ab]; - for (i = n_ab - 1; i >= 0; i--) - p_lo += het_probs[i]; - - double p_hi_lo = p_hi < p_lo ? 2.0 * p_hi : 2.0 * p_lo; - */ - - double p_hwe = 0.0; - /* p-value calculation for p_hwe */ - for (i = 0; i <= rare_copies; i++) - { - if (het_probs[i] > het_probs[n_ab]) - continue; - p_hwe += het_probs[i]; - } - - p_hwe = p_hwe > 1.0 ? 1.0 : p_hwe; - - free(het_probs); - - return p_hwe; -} - - - - - - - - diff --git a/mathfunc.h b/mathfunc.h deleted file mode 100644 index d0e1696..0000000 --- a/mathfunc.h +++ /dev/null @@ -1,41 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - -#ifndef __MATHFUNC_H__ -#define __MATHFUNC_H__ - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - - -using namespace std; - -double VectorVar (const gsl_vector *v); -void CenterMatrix (gsl_matrix *G); -void CenterMatrix (gsl_matrix *G, gsl_vector *w); -void ScaleMatrix (gsl_matrix *G); -double CenterVector (gsl_vector *y); -void CalcUtX (const gsl_matrix *U, gsl_matrix *UtX); -void CalcUtX (const gsl_matrix *U, const gsl_matrix *X, gsl_matrix *UtX); -void CalcUtX (const gsl_matrix *U, const gsl_vector *x, gsl_vector *Utx); -double CalcHWE (const size_t n_hom1, const size_t n_hom2, const size_t n_ab); -void Kronecker(const gsl_matrix *K, const gsl_matrix *V, gsl_matrix *H); -void KroneckerSym(const gsl_matrix *K, const gsl_matrix *V, gsl_matrix *H); - - -#endif diff --git a/mvlmm.cpp b/mvlmm.cpp deleted file mode 100644 index 4b910ee..0000000 --- a/mvlmm.cpp +++ /dev/null @@ -1,3749 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - - - -#include <iostream> -#include <fstream> -#include <sstream> - -#include <iomanip> -#include <cmath> -#include <iostream> -#include <stdio.h> -#include <stdlib.h> -#include <bitset> -#include <cstring> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" - -#include "gsl/gsl_cdf.h" -#include "gsl/gsl_roots.h" -#include "gsl/gsl_min.h" -#include "gsl/gsl_integration.h" - -#include "io.h" -#include "lapack.h" -#include "gzstream.h" - -#ifdef FORCE_FLOAT -#include "lmm_float.h" -#include "mvlmm_float.h" -#else -#include "lmm.h" -#include "mvlmm.h" -#endif - - - -using namespace std; - - -//in this file, X, Y are already transformed (i.e. UtX and UtY) - - -void MVLMM::CopyFromParam (PARAM &cPar) -{ - a_mode=cPar.a_mode; - d_pace=cPar.d_pace; - - file_bfile=cPar.file_bfile; - file_geno=cPar.file_geno; - file_out=cPar.file_out; - path_out=cPar.path_out; - - l_min=cPar.l_min; - l_max=cPar.l_max; - n_region=cPar.n_region; - p_nr=cPar.p_nr; - em_iter=cPar.em_iter; - nr_iter=cPar.nr_iter; - em_prec=cPar.em_prec; - nr_prec=cPar.nr_prec; - crt=cPar.crt; - - Vg_remle_null=cPar.Vg_remle_null; - Ve_remle_null=cPar.Ve_remle_null; - Vg_mle_null=cPar.Vg_mle_null; - Ve_mle_null=cPar.Ve_mle_null; - - time_UtX=0.0; - time_opt=0.0; - - ni_total=cPar.ni_total; - ns_total=cPar.ns_total; - ni_test=cPar.ni_test; - ns_test=cPar.ns_test; - n_cvt=cPar.n_cvt; - - n_ph=cPar.n_ph; - - indicator_idv=cPar.indicator_idv; - indicator_snp=cPar.indicator_snp; - snpInfo=cPar.snpInfo; - - return; -} - - -void MVLMM::CopyToParam (PARAM &cPar) -{ - cPar.time_UtX=time_UtX; - cPar.time_opt=time_opt; - - cPar.Vg_remle_null=Vg_remle_null; - cPar.Ve_remle_null=Ve_remle_null; - cPar.Vg_mle_null=Vg_mle_null; - cPar.Ve_mle_null=Ve_mle_null; - - cPar.VVg_remle_null=VVg_remle_null; - cPar.VVe_remle_null=VVe_remle_null; - cPar.VVg_mle_null=VVg_mle_null; - cPar.VVe_mle_null=VVe_mle_null; - - cPar.beta_remle_null=beta_remle_null; - cPar.se_beta_remle_null=se_beta_remle_null; - cPar.beta_mle_null=beta_mle_null; - cPar.se_beta_mle_null=se_beta_mle_null; - - cPar.logl_remle_H0=logl_remle_H0; - cPar.logl_mle_H0=logl_mle_H0; - return; -} - - -void MVLMM::WriteFiles () -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".assoc.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - outfile<<"chr"<<"\t"<<"rs"<<"\t"<<"ps"<<"\t"<<"n_miss"<<"\t"<<"allele1"<<"\t"<<"allele0"<<"\t"<<"af"<<"\t"; - - for (size_t i=0; i<n_ph; i++) { - outfile<<"beta_"<<i+1<<"\t"; - } - for (size_t i=0; i<n_ph; i++) { - for (size_t j=i; j<n_ph; j++) { - outfile<<"Vbeta_"<<i+1<<"_"<<j+1<<"\t"; - } - } - - if (a_mode==1) { - outfile<<"p_wald"<<endl; - } else if (a_mode==2) { - outfile<<"p_lrt"<<endl; - } else if (a_mode==3) { - outfile<<"p_score"<<endl; - } else if (a_mode==4) { - outfile<<"p_wald"<<"\t"<<"p_lrt"<<"\t"<<"p_score"<<endl; - } else {} - - - size_t t=0, c=0; - for (size_t i=0; i<snpInfo.size(); ++i) { - if (indicator_snp[i]==0) {continue;} - - outfile<<snpInfo[i].chr<<"\t"<<snpInfo[i].rs_number<<"\t"<<snpInfo[i].base_position<<"\t"<<snpInfo[i].n_miss<<"\t"<<snpInfo[i].a_minor<<"\t"<<snpInfo[i].a_major<<"\t"<<fixed<<setprecision(3)<<snpInfo[i].maf<<"\t"; - - outfile<<scientific<<setprecision(6); - - for (size_t i=0; i<n_ph; i++) { - outfile<<sumStat[t].v_beta[i]<<"\t"; - } - - c=0; - for (size_t i=0; i<n_ph; i++) { - for (size_t j=i; j<n_ph; j++) { - outfile<<sumStat[t].v_Vbeta[c]<<"\t"; - c++; - } - } - - if (a_mode==1) { - outfile<<sumStat[t].p_wald <<endl; - } else if (a_mode==2) { - outfile<<sumStat[t].p_lrt<<endl; - } else if (a_mode==3) { - outfile<<sumStat[t].p_score<<endl; - } else if (a_mode==4) { - outfile<<sumStat[t].p_wald <<"\t"<<sumStat[t].p_lrt<<"\t"<<sumStat[t].p_score<<endl; - } else {} - - t++; - } - - - outfile.close(); - outfile.clear(); - return; -} - - - - -//below are functions for EM algorithm - - - - - - -double EigenProc (const gsl_matrix *V_g, const gsl_matrix *V_e, gsl_vector *D_l, gsl_matrix *UltVeh, gsl_matrix *UltVehi) -{ - size_t d_size=V_g->size1; - double d, logdet_Ve=0.0; - - //eigen decomposition of V_e - gsl_matrix *Lambda=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e_temp=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e_h=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e_hi=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *VgVehi=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *U_l=gsl_matrix_alloc (d_size, d_size); - - gsl_matrix_memcpy(V_e_temp, V_e); - EigenDecomp(V_e_temp, U_l, D_l, 0); - - //calculate V_e_h and V_e_hi - gsl_matrix_set_zero(V_e_h); - gsl_matrix_set_zero(V_e_hi); - for (size_t i=0; i<d_size; i++) { - d=gsl_vector_get (D_l, i); - if (d<=0) {continue;} - logdet_Ve+=log(d); - - gsl_vector_view U_col=gsl_matrix_column(U_l, i); - d=sqrt(d); - gsl_blas_dsyr (CblasUpper, d, &U_col.vector, V_e_h); - d=1.0/d; - gsl_blas_dsyr (CblasUpper, d, &U_col.vector, V_e_hi); - } - - //copy the upper part to lower part - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<i; j++) { - gsl_matrix_set (V_e_h, i, j, gsl_matrix_get(V_e_h, j, i)); - gsl_matrix_set (V_e_hi, i, j, gsl_matrix_get(V_e_hi, j, i)); - } - } - - //calculate Lambda=V_ehi V_g V_ehi - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, V_g, V_e_hi, 0.0, VgVehi); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, V_e_hi, VgVehi, 0.0, Lambda); - - //eigen decomposition of Lambda - EigenDecomp(Lambda, U_l, D_l, 0); - - for (size_t i=0; i<d_size; i++) { - d=gsl_vector_get (D_l, i); - if (d<0) {gsl_vector_set (D_l, i, 0);} - } - - //calculate UltVeh and UltVehi - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, U_l, V_e_h, 0.0, UltVeh); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, U_l, V_e_hi, 0.0, UltVehi); - /* - cout<<"Vg: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get (V_g, i, j)<<" "; - } - cout<<endl; - } - cout<<"Ve: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get (V_e, i, j)<<" "; - } - cout<<endl; - } - - cout<<"Dl: "<<endl; - for (size_t i=0; i<d_size; i++) { - cout<<gsl_vector_get (D_l, i)<<endl; - } - cout<<"UltVeh: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get (UltVeh, i, j)<<" "; - } - cout<<endl; - } - */ - - //free memory - gsl_matrix_free (Lambda); - gsl_matrix_free (V_e_temp); - gsl_matrix_free (V_e_h); - gsl_matrix_free (V_e_hi); - gsl_matrix_free (VgVehi); - gsl_matrix_free (U_l); - - return logdet_Ve; -} - -//Qi=(\sum_{k=1}^n x_kx_k^T\otimes(delta_k*Dl+I)^{-1} )^{-1} -double CalcQi (const gsl_vector *eval, const gsl_vector *D_l, const gsl_matrix *X, gsl_matrix *Qi) -{ - size_t n_size=eval->size, d_size=D_l->size, dc_size=Qi->size1; - size_t c_size=dc_size/d_size; - - double delta, dl, d1, d2, d, logdet_Q; - - gsl_matrix *Q=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix_set_zero (Q); - - for (size_t i=0; i<c_size; i++) { - for (size_t j=0; j<c_size; j++) { - for (size_t l=0; l<d_size; l++) { - dl=gsl_vector_get(D_l, l); - - if (j<i) { - d=gsl_matrix_get (Q, j*d_size+l, i*d_size+l); - } else { - d=0.0; - for (size_t k=0; k<n_size; k++) { - d1=gsl_matrix_get(X, i, k); - d2=gsl_matrix_get(X, j, k); - delta=gsl_vector_get(eval, k); - d+=d1*d2/(dl*delta+1.0); - } - } - - gsl_matrix_set (Q, i*d_size+l, j*d_size+l, d); - } - } - } - - //calculate LU decomposition of Q, and invert Q and calculate |Q| - int sig; - gsl_permutation * pmt=gsl_permutation_alloc (dc_size); - LUDecomp (Q, pmt, &sig); - LUInvert (Q, pmt, Qi); - - logdet_Q=LULndet (Q); - - gsl_matrix_free (Q); - gsl_permutation_free (pmt); - - return logdet_Q; -} - -//xHiy=\sum_{k=1}^n x_k\otimes ((delta_k*Dl+I)^{-1}Ul^TVe^{-1/2}y -void CalcXHiY(const gsl_vector *eval, const gsl_vector *D_l, const gsl_matrix *X, const gsl_matrix *UltVehiY, gsl_vector *xHiy) -{ - size_t n_size=eval->size, c_size=X->size1, d_size=D_l->size; - - gsl_vector_set_zero (xHiy); - - double x, delta, dl, y, d; - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - for (size_t j=0; j<c_size; j++) { - d=0.0; - for (size_t k=0; k<n_size; k++) { - x=gsl_matrix_get(X, j, k); - y=gsl_matrix_get(UltVehiY, i, k); - delta=gsl_vector_get(eval, k); - d+=x*y/(delta*dl+1.0); - } - gsl_vector_set(xHiy, j*d_size+i, d); - } - } - /* - cout<<"xHiy: "<<endl; - for (size_t i=0; i<(d_size*c_size); i++) { - cout<<gsl_vector_get(xHiy, i)<<endl; - } - */ - return; -} - - -//OmegaU=D_l/(delta Dl+I)^{-1} -//OmegaE=delta D_l/(delta Dl+I)^{-1} -void CalcOmega (const gsl_vector *eval, const gsl_vector *D_l, gsl_matrix *OmegaU, gsl_matrix *OmegaE) -{ - size_t n_size=eval->size, d_size=D_l->size; - double delta, dl, d_u, d_e; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - - d_u=dl/(delta*dl+1.0); - d_e=delta*d_u; - - gsl_matrix_set(OmegaU, i, k, d_u); - gsl_matrix_set(OmegaE, i, k, d_e); - } - } - - return; -} - - -void UpdateU (const gsl_matrix *OmegaE, const gsl_matrix *UltVehiY, const gsl_matrix *UltVehiBX, gsl_matrix *UltVehiU) -{ - gsl_matrix_memcpy (UltVehiU, UltVehiY); - gsl_matrix_sub (UltVehiU, UltVehiBX); - - gsl_matrix_mul_elements (UltVehiU, OmegaE); - return; -} - - -void UpdateE (const gsl_matrix *UltVehiY, const gsl_matrix *UltVehiBX, const gsl_matrix *UltVehiU, gsl_matrix *UltVehiE) -{ - gsl_matrix_memcpy (UltVehiE, UltVehiY); - gsl_matrix_sub (UltVehiE, UltVehiBX); - gsl_matrix_sub (UltVehiE, UltVehiU); - - return; -} - - - -void UpdateL_B (const gsl_matrix *X, const gsl_matrix *XXti, const gsl_matrix *UltVehiY, const gsl_matrix *UltVehiU, gsl_matrix *UltVehiBX, gsl_matrix *UltVehiB) -{ - size_t c_size=X->size1, d_size=UltVehiY->size1; - - gsl_matrix *YUX=gsl_matrix_alloc (d_size, c_size); - - gsl_matrix_memcpy (UltVehiBX, UltVehiY); - gsl_matrix_sub (UltVehiBX, UltVehiU); - - gsl_blas_dgemm(CblasNoTrans, CblasTrans, 1.0, UltVehiBX, X, 0.0, YUX); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, YUX, XXti, 0.0, UltVehiB); - - gsl_matrix_free(YUX); - - return; -} - -void UpdateRL_B (const gsl_vector *xHiy, const gsl_matrix *Qi, gsl_matrix *UltVehiB) -{ - size_t d_size=UltVehiB->size1, c_size=UltVehiB->size2, dc_size=Qi->size1; - - gsl_vector *b=gsl_vector_alloc (dc_size); - - //calculate b=Qiv - gsl_blas_dgemv(CblasNoTrans, 1.0, Qi, xHiy, 0.0, b); - - //copy b to UltVehiB - for (size_t i=0; i<c_size; i++) { - gsl_vector_view UltVehiB_col=gsl_matrix_column (UltVehiB, i); - gsl_vector_const_view b_subcol=gsl_vector_const_subvector (b, i*d_size, d_size); - gsl_vector_memcpy (&UltVehiB_col.vector, &b_subcol.vector); - } - - gsl_vector_free(b); - - return; -} - - - -void UpdateV (const gsl_vector *eval, const gsl_matrix *U, const gsl_matrix *E, const gsl_matrix *Sigma_uu, const gsl_matrix *Sigma_ee, gsl_matrix *V_g, gsl_matrix *V_e) -{ - size_t n_size=eval->size, d_size=U->size1; - - gsl_matrix_set_zero (V_g); - gsl_matrix_set_zero (V_e); - - double delta; - - //calculate the first part: UD^{-1}U^T and EE^T - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - if (delta==0) {continue;} - - gsl_vector_const_view U_col=gsl_matrix_const_column (U, k); - gsl_blas_dsyr (CblasUpper, 1.0/delta, &U_col.vector, V_g); - } - - gsl_blas_dsyrk(CblasUpper, CblasNoTrans, 1.0, E, 0.0, V_e); - - //copy the upper part to lower part - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<i; j++) { - gsl_matrix_set (V_g, i, j, gsl_matrix_get(V_g, j, i)); - gsl_matrix_set (V_e, i, j, gsl_matrix_get(V_e, j, i)); - } - } - - //add Sigma - gsl_matrix_add (V_g, Sigma_uu); - gsl_matrix_add (V_e, Sigma_ee); - - //scale by 1/n - gsl_matrix_scale (V_g, 1.0/(double)n_size); - gsl_matrix_scale (V_e, 1.0/(double)n_size); - - return; -} - - -void CalcSigma (const char func_name, const gsl_vector *eval, const gsl_vector *D_l, const gsl_matrix *X, const gsl_matrix *OmegaU, const gsl_matrix *OmegaE, const gsl_matrix *UltVeh, const gsl_matrix *Qi, gsl_matrix *Sigma_uu, gsl_matrix *Sigma_ee) -{ - if (func_name!='R' && func_name!='L' && func_name!='r' && func_name!='l') {cout<<"func_name only takes 'R' or 'L': 'R' for log-restricted likelihood, 'L' for log-likelihood."<<endl; return;} - - size_t n_size=eval->size, c_size=X->size1, d_size=D_l->size, dc_size=Qi->size1; - - gsl_matrix_set_zero(Sigma_uu); - gsl_matrix_set_zero(Sigma_ee); - - double delta, dl, x, d; - - //calculate the first diagonal term - gsl_vector_view Suu_diag=gsl_matrix_diagonal (Sigma_uu); - gsl_vector_view See_diag=gsl_matrix_diagonal (Sigma_ee); - - for (size_t k=0; k<n_size; k++) { - gsl_vector_const_view OmegaU_col=gsl_matrix_const_column (OmegaU, k); - gsl_vector_const_view OmegaE_col=gsl_matrix_const_column (OmegaE, k); - - gsl_vector_add (&Suu_diag.vector, &OmegaU_col.vector); - gsl_vector_add (&See_diag.vector, &OmegaE_col.vector); - } - - //calculate the second term for reml - if (func_name=='R' || func_name=='r') { - gsl_matrix *M_u=gsl_matrix_alloc(dc_size, d_size); - gsl_matrix *M_e=gsl_matrix_alloc(dc_size, d_size); - gsl_matrix *QiM=gsl_matrix_alloc(dc_size, d_size); - - gsl_matrix_set_zero(M_u); - gsl_matrix_set_zero(M_e); - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - //if (delta==0) {continue;} - - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - for (size_t j=0; j<c_size; j++) { - x=gsl_matrix_get(X, j, k); - d=x/(delta*dl+1.0); - gsl_matrix_set(M_e, j*d_size+i, i, d); - gsl_matrix_set(M_u, j*d_size+i, i, d*dl); - } - } - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Qi, M_u, 0.0, QiM); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, delta, M_u, QiM, 1.0, Sigma_uu); - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Qi, M_e, 0.0, QiM); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, M_e, QiM, 1.0, Sigma_ee); - } - - gsl_matrix_free(M_u); - gsl_matrix_free(M_e); - gsl_matrix_free(QiM); - } - - //multiply both sides by VehUl - gsl_matrix *M=gsl_matrix_alloc (d_size, d_size); - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Sigma_uu, UltVeh, 0.0, M); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, M, 0.0, Sigma_uu); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Sigma_ee, UltVeh, 0.0, M); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, M, 0.0, Sigma_ee); - - gsl_matrix_free(M); - return; -} - - -//'R' for restricted likelihood and 'L' for likelihood -//'R' update B and 'L' don't -//only calculate -0.5*\sum_{k=1}^n|H_k|-0.5yPxy -double MphCalcLogL (const gsl_vector *eval, const gsl_vector *xHiy, const gsl_vector *D_l, const gsl_matrix *UltVehiY, const gsl_matrix *Qi) -{ - size_t n_size=eval->size, d_size=D_l->size, dc_size=Qi->size1; - double logl=0.0, delta, dl, y, d; - - //calculate yHiy+log|H_k| - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - for (size_t i=0; i<d_size; i++) { - y=gsl_matrix_get(UltVehiY, i, k); - dl=gsl_vector_get(D_l, i); - d=delta*dl+1.0; - - logl+=y*y/d+log(d); - } - } - - //calculate the rest of yPxy - gsl_vector *Qiv=gsl_vector_alloc(dc_size); - - gsl_blas_dgemv(CblasNoTrans, 1.0, Qi, xHiy, 0.0, Qiv); - gsl_blas_ddot(xHiy, Qiv, &d); - - logl-=d; - - gsl_vector_free(Qiv); - - return -0.5*logl; -} - - - - - -//Y is a dxn matrix, X is a cxn matrix, B is a dxc matrix, V_g is a dxd matrix, V_e is a dxd matrix, eval is a size n vector -//'R' for restricted likelihood and 'L' for likelihood -double MphEM (const char func_name, const size_t max_iter, const double max_prec, const gsl_vector *eval, const gsl_matrix *X, const gsl_matrix *Y, gsl_matrix *U_hat, gsl_matrix *E_hat, gsl_matrix *OmegaU, gsl_matrix *OmegaE, gsl_matrix *UltVehiY, gsl_matrix *UltVehiBX, gsl_matrix *UltVehiU, gsl_matrix *UltVehiE, gsl_matrix *V_g, gsl_matrix *V_e, gsl_matrix *B) -{ - if (func_name!='R' && func_name!='L' && func_name!='r' && func_name!='l') {cout<<"func_name only takes 'R' or 'L': 'R' for log-restricted likelihood, 'L' for log-likelihood."<<endl; return 0.0;} - - size_t n_size=eval->size, c_size=X->size1, d_size=Y->size1; - size_t dc_size=d_size*c_size; - - gsl_matrix *XXt=gsl_matrix_alloc (c_size, c_size); - gsl_matrix *XXti=gsl_matrix_alloc (c_size, c_size); - gsl_vector *D_l=gsl_vector_alloc (d_size); - gsl_matrix *UltVeh=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVehi=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVehiB=gsl_matrix_alloc (d_size, c_size); - gsl_matrix *Qi=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *Sigma_uu=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *Sigma_ee=gsl_matrix_alloc (d_size, d_size); - gsl_vector *xHiy=gsl_vector_alloc (dc_size); - gsl_permutation * pmt=gsl_permutation_alloc (c_size); - - double logl_const=0.0, logl_old=0.0, logl_new=0.0, logdet_Q, logdet_Ve; - int sig; - - //calculate |XXt| and (XXt)^{-1} - gsl_blas_dsyrk (CblasUpper, CblasNoTrans, 1.0, X, 0.0, XXt); - for (size_t i=0; i<c_size; ++i) { - for (size_t j=0; j<i; ++j) { - gsl_matrix_set (XXt, i, j, gsl_matrix_get (XXt, j, i)); - } - } - - LUDecomp (XXt, pmt, &sig); - LUInvert (XXt, pmt, XXti); - - //calculate the constant for logl - if (func_name=='R' || func_name=='r') { - logl_const=-0.5*(double)(n_size-c_size)*(double)d_size*log(2.0*M_PI)+0.5*(double)d_size*LULndet (XXt); - } else { - logl_const=-0.5*(double)n_size*(double)d_size*log(2.0*M_PI); - } - - //start EM - for (size_t t=0; t<max_iter; t++) { - logdet_Ve=EigenProc (V_g, V_e, D_l, UltVeh, UltVehi); - - logdet_Q=CalcQi (eval, D_l, X, Qi); - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehi, Y, 0.0, UltVehiY); - CalcXHiY(eval, D_l, X, UltVehiY, xHiy); - - //calculate log likelihood/restricted likelihood value, and terminate if change is small - logl_new=logl_const+MphCalcLogL (eval, xHiy, D_l, UltVehiY, Qi)-0.5*(double)n_size*logdet_Ve; - if (func_name=='R' || func_name=='r') { - logl_new+=-0.5*(logdet_Q-(double)c_size*logdet_Ve); - } - if (t!=0 && abs(logl_new-logl_old)<max_prec) {break;} - logl_old=logl_new; - - /* - cout<<"iteration = "<<t<<" log-likelihood = "<<logl_old<<"\t"<<logl_new<<endl; - - cout<<"Vg: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get(V_g, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"Ve: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get(V_e, i, j)<<"\t"; - } - cout<<endl; - } - */ - - CalcOmega (eval, D_l, OmegaU, OmegaE); - - //Update UltVehiB, UltVehiU - if (func_name=='R' || func_name=='r') { - UpdateRL_B(xHiy, Qi, UltVehiB); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehiB, X, 0.0, UltVehiBX); - } else if (t==0) { - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehi, B, 0.0, UltVehiB); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehiB, X, 0.0, UltVehiBX); - } - - UpdateU(OmegaE, UltVehiY, UltVehiBX, UltVehiU); - - if (func_name=='L' || func_name=='l') { - //UltVehiBX is destroyed here - UpdateL_B(X, XXti, UltVehiY, UltVehiU, UltVehiBX, UltVehiB); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehiB, X, 0.0, UltVehiBX); - } - - UpdateE(UltVehiY, UltVehiBX, UltVehiU, UltVehiE); - - //calculate U_hat, E_hat and B - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, UltVehiU, 0.0, U_hat); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, UltVehiE, 0.0, E_hat); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, UltVehiB, 0.0, B); - - //calculate Sigma_uu and Sigma_ee - CalcSigma (func_name, eval, D_l, X, OmegaU, OmegaE, UltVeh, Qi, Sigma_uu, Sigma_ee); - - //update V_g and V_e - UpdateV (eval, U_hat, E_hat, Sigma_uu, Sigma_ee, V_g, V_e); - } - - gsl_matrix_free(XXt); - gsl_matrix_free(XXti); - gsl_vector_free(D_l); - gsl_matrix_free(UltVeh); - gsl_matrix_free(UltVehi); - gsl_matrix_free(UltVehiB); - gsl_matrix_free(Qi); - gsl_matrix_free(Sigma_uu); - gsl_matrix_free(Sigma_ee); - gsl_vector_free(xHiy); - gsl_permutation_free(pmt); - - return logl_new; -} - - - - - - - -//calculate p-value, beta (d by 1 vector) and V(beta) -double MphCalcP (const gsl_vector *eval, const gsl_vector *x_vec, const gsl_matrix *W, const gsl_matrix *Y, const gsl_matrix *V_g, const gsl_matrix *V_e, gsl_matrix *UltVehiY, gsl_vector *beta, gsl_matrix *Vbeta) -{ - size_t n_size=eval->size, c_size=W->size1, d_size=V_g->size1; - size_t dc_size=d_size*c_size; - double delta, dl, d, d1, d2, dy, dx, dw, logdet_Ve, logdet_Q, p_value; - - gsl_vector *D_l=gsl_vector_alloc (d_size); - gsl_matrix *UltVeh=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVehi=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *Qi=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *WHix=gsl_matrix_alloc (dc_size, d_size); - gsl_matrix *QiWHix=gsl_matrix_alloc(dc_size, d_size); - - gsl_matrix *xPx=gsl_matrix_alloc (d_size, d_size); - gsl_vector *xPy=gsl_vector_alloc (d_size); - //gsl_vector *UltVehiy=gsl_vector_alloc (d_size); - gsl_vector *WHiy=gsl_vector_alloc (dc_size); - - gsl_matrix_set_zero (xPx); - gsl_matrix_set_zero (WHix); - gsl_vector_set_zero (xPy); - gsl_vector_set_zero (WHiy); - - //eigen decomposition and calculate log|Ve| - logdet_Ve=EigenProc (V_g, V_e, D_l, UltVeh, UltVehi); - - //calculate Qi and log|Q| - logdet_Q=CalcQi (eval, D_l, W, Qi); - - //calculate UltVehiY - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehi, Y, 0.0, UltVehiY); - - //calculate WHix, WHiy, xHiy, xHix - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - - d1=0.0; d2=0.0; - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - dx=gsl_vector_get(x_vec, k); - dy=gsl_matrix_get(UltVehiY, i, k); - - d1+=dx*dy/(delta*dl+1.0); - d2+=dx*dx/(delta*dl+1.0); - } - gsl_vector_set (xPy, i, d1); - gsl_matrix_set (xPx, i, i, d2); - - for (size_t j=0; j<c_size; j++) { - d1=0.0; d2=0.0; - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - dx=gsl_vector_get(x_vec, k); - dw=gsl_matrix_get(W, j, k); - dy=gsl_matrix_get(UltVehiY, i, k); - - //if (delta==0) {continue;} - d1+=dx*dw/(delta*dl+1.0); - d2+=dy*dw/(delta*dl+1.0); - } - gsl_matrix_set(WHix, j*d_size+i, i, d1); - gsl_vector_set(WHiy, j*d_size+i, d2); - } - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Qi, WHix, 0.0, QiWHix); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, -1.0, WHix, QiWHix, 1.0, xPx); - gsl_blas_dgemv(CblasTrans, -1.0, QiWHix, WHiy, 1.0, xPy); - - //calculate V(beta) and beta - int sig; - gsl_permutation * pmt=gsl_permutation_alloc (d_size); - LUDecomp (xPx, pmt, &sig); - LUSolve (xPx, pmt, xPy, D_l); - LUInvert (xPx, pmt, Vbeta); - - //need to multiply UltVehi on both sides or one side - gsl_blas_dgemv(CblasTrans, 1.0, UltVeh, D_l, 0.0, beta); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Vbeta, UltVeh, 0.0, xPx); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, xPx, 0.0, Vbeta); - - //calculate test statistic and p value - gsl_blas_ddot(D_l, xPy, &d); - - p_value=gsl_cdf_chisq_Q (d, (double)d_size); - //d*=(double)(n_size-c_size-d_size)/((double)d_size*(double)(n_size-c_size-1)); - //p_value=gsl_cdf_fdist_Q (d, (double)d_size, (double)(n_size-c_size-d_size)); - - gsl_vector_free(D_l); - gsl_matrix_free(UltVeh); - gsl_matrix_free(UltVehi); - gsl_matrix_free(Qi); - gsl_matrix_free(WHix); - gsl_matrix_free(QiWHix); - - gsl_matrix_free(xPx); - gsl_vector_free(xPy); - gsl_vector_free(WHiy); - - gsl_permutation_free(pmt); - - return p_value; -} - - - -//calculate B and its standard error (which is a matrix of the same dimension as B) -void MphCalcBeta (const gsl_vector *eval, const gsl_matrix *W, const gsl_matrix *Y, const gsl_matrix *V_g, const gsl_matrix *V_e, gsl_matrix *UltVehiY, gsl_matrix *B, gsl_matrix *se_B) -{ - size_t n_size=eval->size, c_size=W->size1, d_size=V_g->size1; - size_t dc_size=d_size*c_size; - double delta, dl, d, dy, dw, logdet_Ve, logdet_Q; - - gsl_vector *D_l=gsl_vector_alloc (d_size); - gsl_matrix *UltVeh=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVehi=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *Qi=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *Qi_temp=gsl_matrix_alloc (dc_size, dc_size); - //gsl_vector *UltVehiy=gsl_vector_alloc (d_size); - gsl_vector *WHiy=gsl_vector_alloc (dc_size); - gsl_vector *QiWHiy=gsl_vector_alloc (dc_size); - gsl_vector *beta=gsl_vector_alloc (dc_size); - gsl_matrix *Vbeta=gsl_matrix_alloc (dc_size, dc_size); - - gsl_vector_set_zero (WHiy); - - //eigen decomposition and calculate log|Ve| - logdet_Ve=EigenProc (V_g, V_e, D_l, UltVeh, UltVehi); - - //calculate Qi and log|Q| - logdet_Q=CalcQi (eval, D_l, W, Qi); - - //calculate UltVehiY - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehi, Y, 0.0, UltVehiY); - - //calculate WHiy - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - - for (size_t j=0; j<c_size; j++) { - d=0.0; - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - dw=gsl_matrix_get(W, j, k); - dy=gsl_matrix_get(UltVehiY, i, k); - - //if (delta==0) {continue;} - d+=dy*dw/(delta*dl+1.0); - } - gsl_vector_set(WHiy, j*d_size+i, d); - } - } - - gsl_blas_dgemv(CblasNoTrans, 1.0, Qi, WHiy, 0.0, QiWHiy); - - //need to multiply I_c\otimes UltVehi on both sides or one side - for (size_t i=0; i<c_size; i++) { - gsl_vector_view QiWHiy_sub=gsl_vector_subvector(QiWHiy, i*d_size, d_size); - gsl_vector_view beta_sub=gsl_vector_subvector(beta, i*d_size, d_size); - gsl_blas_dgemv(CblasTrans, 1.0, UltVeh, &QiWHiy_sub.vector, 0.0, &beta_sub.vector); - - for (size_t j=0; j<c_size; j++) { - gsl_matrix_view Qi_sub=gsl_matrix_submatrix (Qi, i*d_size, j*d_size, d_size, d_size); - gsl_matrix_view Qitemp_sub=gsl_matrix_submatrix (Qi_temp, i*d_size, j*d_size, d_size, d_size); - gsl_matrix_view Vbeta_sub=gsl_matrix_submatrix (Vbeta, i*d_size, j*d_size, d_size, d_size); - - if (j<i) { - gsl_matrix_view Vbeta_sym=gsl_matrix_submatrix (Vbeta, j*d_size, i*d_size, d_size, d_size); - gsl_matrix_transpose_memcpy (&Vbeta_sub.matrix, &Vbeta_sym.matrix); - } else { - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &Qi_sub.matrix, UltVeh, 0.0, &Qitemp_sub.matrix); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, &Qitemp_sub.matrix, 0.0, &Vbeta_sub.matrix); - } - } - } - - //copy beta to B, and Vbeta to se_B - for (size_t j=0; j<B->size2; j++) { - for (size_t i=0; i<B->size1; i++) { - gsl_matrix_set(B, i, j, gsl_vector_get(beta, j*d_size+i)); - gsl_matrix_set(se_B, i, j, sqrt(gsl_matrix_get(Vbeta, j*d_size+i, j*d_size+i))); - } - } - - //free matrices - gsl_vector_free(D_l); - gsl_matrix_free(UltVeh); - gsl_matrix_free(UltVehi); - gsl_matrix_free(Qi); - gsl_matrix_free(Qi_temp); - gsl_vector_free(WHiy); - gsl_vector_free(QiWHiy); - gsl_vector_free(beta); - gsl_matrix_free(Vbeta); - - return; -} - - - -//below are functions for Newton-Raphson's algorithm - - - - - -//calculate all Hi and return logdet_H=\sum_{k=1}^{n}log|H_k| -//and calculate Qi and return logdet_Q -//and calculate yPy -void CalcHiQi (const gsl_vector *eval, const gsl_matrix *X, const gsl_matrix *V_g, const gsl_matrix *V_e, gsl_matrix *Hi_all, gsl_matrix *Qi, double &logdet_H, double &logdet_Q) -{ - gsl_matrix_set_zero (Hi_all); - gsl_matrix_set_zero (Qi); - logdet_H=0.0; logdet_Q=0.0; - - size_t n_size=eval->size, c_size=X->size1, d_size=V_g->size1; - double logdet_Ve=0.0, delta, dl, d; - - gsl_matrix *mat_dd=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVeh=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVehi=gsl_matrix_alloc (d_size, d_size); - gsl_vector *D_l=gsl_vector_alloc (d_size); - - //calculate D_l, UltVeh and UltVehi - logdet_Ve=EigenProc (V_g, V_e, D_l, UltVeh, UltVehi); - - //calculate each Hi and log|H_k| - logdet_H=(double)n_size*logdet_Ve; - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - gsl_matrix_memcpy (mat_dd, UltVehi); - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - d=delta*dl+1.0; - - gsl_vector_view mat_row=gsl_matrix_row (mat_dd, i); - gsl_vector_scale (&mat_row.vector, 1.0/d); - - logdet_H+=log(d); - } - - gsl_matrix_view Hi_k=gsl_matrix_submatrix(Hi_all, 0, k*d_size, d_size, d_size); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVehi, mat_dd, 0.0, &Hi_k.matrix); - } - - //calculate Qi, and multiply I\otimes UtVeh on both side - //and calculate logdet_Q, don't forget to substract c_size*logdet_Ve - logdet_Q=CalcQi (eval, D_l, X, Qi)-(double)c_size*logdet_Ve; - - for (size_t i=0; i<c_size; i++) { - for (size_t j=0; j<c_size; j++) { - gsl_matrix_view Qi_sub=gsl_matrix_submatrix (Qi, i*d_size, j*d_size, d_size, d_size); - if (j<i) { - gsl_matrix_view Qi_sym=gsl_matrix_submatrix (Qi, j*d_size, i*d_size, d_size, d_size); - gsl_matrix_transpose_memcpy (&Qi_sub.matrix, &Qi_sym.matrix); - } else { - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &Qi_sub.matrix, UltVeh, 0.0, mat_dd); - gsl_blas_dgemm(CblasTrans, CblasNoTrans, 1.0, UltVeh, mat_dd, 0.0, &Qi_sub.matrix); - } - } - } - - //free memory - gsl_matrix_free(mat_dd); - gsl_matrix_free(UltVeh); - gsl_matrix_free(UltVehi); - gsl_vector_free(D_l); - - return; -} - - - - -//calculate all Hiy -void Calc_Hiy_all (const gsl_matrix *Y, const gsl_matrix *Hi_all, gsl_matrix *Hiy_all) -{ - gsl_matrix_set_zero (Hiy_all); - - size_t n_size=Y->size2, d_size=Y->size1; - - for (size_t k=0; k<n_size; k++) { - gsl_matrix_const_view Hi_k=gsl_matrix_const_submatrix(Hi_all, 0, k*d_size, d_size, d_size); - gsl_vector_const_view y_k=gsl_matrix_const_column(Y, k); - gsl_vector_view Hiy_k=gsl_matrix_column(Hiy_all, k); - - gsl_blas_dgemv (CblasNoTrans, 1.0, &Hi_k.matrix, &y_k.vector, 0.0, &Hiy_k.vector); - } - - return; -} - - -//calculate all xHi -void Calc_xHi_all (const gsl_matrix *X, const gsl_matrix *Hi_all, gsl_matrix *xHi_all) -{ - gsl_matrix_set_zero (xHi_all); - - size_t n_size=X->size2, c_size=X->size1, d_size=Hi_all->size1; - - double d; - - for (size_t k=0; k<n_size; k++) { - gsl_matrix_const_view Hi_k=gsl_matrix_const_submatrix(Hi_all, 0, k*d_size, d_size, d_size); - - for (size_t i=0; i<c_size; i++) { - d=gsl_matrix_get (X, i, k); - gsl_matrix_view xHi_sub=gsl_matrix_submatrix(xHi_all, i*d_size, k*d_size, d_size, d_size); - gsl_matrix_memcpy(&xHi_sub.matrix, &Hi_k.matrix); - gsl_matrix_scale(&xHi_sub.matrix, d); - } - } - - return; -} - - -//calculate scalar yHiy -double Calc_yHiy (const gsl_matrix *Y, const gsl_matrix *Hiy_all) -{ - double yHiy=0.0, d; - size_t n_size=Y->size2; - - for (size_t k=0; k<n_size; k++) { - gsl_vector_const_view y_k=gsl_matrix_const_column(Y, k); - gsl_vector_const_view Hiy_k=gsl_matrix_const_column(Hiy_all, k); - - gsl_blas_ddot (&Hiy_k.vector, &y_k.vector, &d); - yHiy+=d; - } - - return yHiy; -} - - -//calculate the vector xHiy -void Calc_xHiy (const gsl_matrix *Y, const gsl_matrix *xHi, gsl_vector *xHiy) -{ - gsl_vector_set_zero (xHiy); - - size_t n_size=Y->size2, d_size=Y->size1, dc_size=xHi->size1; - - for (size_t k=0; k<n_size; k++) { - gsl_matrix_const_view xHi_k=gsl_matrix_const_submatrix(xHi, 0, k*d_size, dc_size, d_size); - gsl_vector_const_view y_k=gsl_matrix_const_column(Y, k); - - gsl_blas_dgemv (CblasNoTrans, 1.0, &xHi_k.matrix, &y_k.vector, 1.0, xHiy); - } - - return; -} - - - - -//0<=i,j<d_size -size_t GetIndex (const size_t i, const size_t j, const size_t d_size) -{ - if (i>=d_size || j>=d_size) {cout<<"error in GetIndex."<<endl; return 0;} - - size_t s, l; - if (j<i) {s=j; l=i;} else {s=i; l=j;} - - return (2*d_size-s+1)*s/2+l-s; -} - - - -void Calc_yHiDHiy (const gsl_vector *eval, const gsl_matrix *Hiy, const size_t i, const size_t j, double &yHiDHiy_g, double &yHiDHiy_e) -{ - yHiDHiy_g=0.0; - yHiDHiy_e=0.0; - - size_t n_size=eval->size; - - double delta, d1, d2; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - d1=gsl_matrix_get (Hiy, i, k); - d2=gsl_matrix_get (Hiy, j, k); - - if (i==j) { - yHiDHiy_g+=delta*d1*d2; - yHiDHiy_e+=d1*d2; - } else { - yHiDHiy_g+=delta*d1*d2*2.0; - yHiDHiy_e+=d1*d2*2.0; - } - } - - return; -} - - - -void Calc_xHiDHiy (const gsl_vector *eval, const gsl_matrix *xHi, const gsl_matrix *Hiy, const size_t i, const size_t j, gsl_vector *xHiDHiy_g, gsl_vector *xHiDHiy_e) -{ - gsl_vector_set_zero(xHiDHiy_g); - gsl_vector_set_zero(xHiDHiy_e); - - size_t n_size=eval->size, d_size=Hiy->size1; - - double delta, d; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - gsl_vector_const_view xHi_col_i=gsl_matrix_const_column (xHi, k*d_size+i); - d=gsl_matrix_get (Hiy, j, k); - - gsl_blas_daxpy (d*delta, &xHi_col_i.vector, xHiDHiy_g); - gsl_blas_daxpy (d, &xHi_col_i.vector, xHiDHiy_e); - - if (i!=j) { - gsl_vector_const_view xHi_col_j=gsl_matrix_const_column (xHi, k*d_size+j); - d=gsl_matrix_get (Hiy, i, k); - - gsl_blas_daxpy (d*delta, &xHi_col_j.vector, xHiDHiy_g); - gsl_blas_daxpy (d, &xHi_col_j.vector, xHiDHiy_e); - } - } - - return; -} - - -void Calc_xHiDHix (const gsl_vector *eval, const gsl_matrix *xHi, const size_t i, const size_t j, gsl_matrix *xHiDHix_g, gsl_matrix *xHiDHix_e) -{ - gsl_matrix_set_zero(xHiDHix_g); - gsl_matrix_set_zero(xHiDHix_e); - - size_t n_size=eval->size, dc_size=xHi->size1; - size_t d_size=xHi->size2/n_size; - - double delta; - - gsl_matrix *mat_dcdc=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *mat_dcdc_t=gsl_matrix_alloc (dc_size, dc_size); - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - gsl_vector_const_view xHi_col_i=gsl_matrix_const_column (xHi, k*d_size+i); - gsl_vector_const_view xHi_col_j=gsl_matrix_const_column (xHi, k*d_size+j); - - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (1.0, &xHi_col_i.vector, &xHi_col_j.vector, mat_dcdc); - - gsl_matrix_transpose_memcpy (mat_dcdc_t, mat_dcdc); - - gsl_matrix_add (xHiDHix_e, mat_dcdc); - - gsl_matrix_scale (mat_dcdc, delta); - gsl_matrix_add (xHiDHix_g, mat_dcdc); - - if (i!=j) { - gsl_matrix_add (xHiDHix_e, mat_dcdc_t); - - gsl_matrix_scale (mat_dcdc_t, delta); - gsl_matrix_add (xHiDHix_g, mat_dcdc_t); - } - } - - gsl_matrix_free(mat_dcdc); - gsl_matrix_free(mat_dcdc_t); - - return; -} - - - -void Calc_yHiDHiDHiy (const gsl_vector *eval, const gsl_matrix *Hi, const gsl_matrix *Hiy, const size_t i1, const size_t j1, const size_t i2, const size_t j2, double &yHiDHiDHiy_gg, double &yHiDHiDHiy_ee, double &yHiDHiDHiy_ge) -{ - yHiDHiDHiy_gg=0.0; - yHiDHiDHiy_ee=0.0; - yHiDHiDHiy_ge=0.0; - - size_t n_size=eval->size, d_size=Hiy->size1; - - double delta, d_Hiy_i1, d_Hiy_j1, d_Hiy_i2, d_Hiy_j2, d_Hi_i1i2, d_Hi_i1j2, d_Hi_j1i2, d_Hi_j1j2; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - d_Hiy_i1=gsl_matrix_get (Hiy, i1, k); - d_Hiy_j1=gsl_matrix_get (Hiy, j1, k); - d_Hiy_i2=gsl_matrix_get (Hiy, i2, k); - d_Hiy_j2=gsl_matrix_get (Hiy, j2, k); - - d_Hi_i1i2=gsl_matrix_get (Hi, i1, k*d_size+i2); - d_Hi_i1j2=gsl_matrix_get (Hi, i1, k*d_size+j2); - d_Hi_j1i2=gsl_matrix_get (Hi, j1, k*d_size+i2); - d_Hi_j1j2=gsl_matrix_get (Hi, j1, k*d_size+j2); - - if (i1==j1) { - yHiDHiDHiy_gg+=delta*delta*(d_Hiy_i1*d_Hi_j1i2*d_Hiy_j2); - yHiDHiDHiy_ee+=(d_Hiy_i1*d_Hi_j1i2*d_Hiy_j2); - yHiDHiDHiy_ge+=delta*(d_Hiy_i1*d_Hi_j1i2*d_Hiy_j2); - - if (i2!=j2) { - yHiDHiDHiy_gg+=delta*delta*(d_Hiy_i1*d_Hi_j1j2*d_Hiy_i2); - yHiDHiDHiy_ee+=(d_Hiy_i1*d_Hi_j1j2*d_Hiy_i2); - yHiDHiDHiy_ge+=delta*(d_Hiy_i1*d_Hi_j1j2*d_Hiy_i2); - } - } else { - yHiDHiDHiy_gg+=delta*delta*(d_Hiy_i1*d_Hi_j1i2*d_Hiy_j2+d_Hiy_j1*d_Hi_i1i2*d_Hiy_j2); - yHiDHiDHiy_ee+=(d_Hiy_i1*d_Hi_j1i2*d_Hiy_j2+d_Hiy_j1*d_Hi_i1i2*d_Hiy_j2); - yHiDHiDHiy_ge+=delta*(d_Hiy_i1*d_Hi_j1i2*d_Hiy_j2+d_Hiy_j1*d_Hi_i1i2*d_Hiy_j2); - - if (i2!=j2) { - yHiDHiDHiy_gg+=delta*delta*(d_Hiy_i1*d_Hi_j1j2*d_Hiy_i2+d_Hiy_j1*d_Hi_i1j2*d_Hiy_i2); - yHiDHiDHiy_ee+=(d_Hiy_i1*d_Hi_j1j2*d_Hiy_i2+d_Hiy_j1*d_Hi_i1j2*d_Hiy_i2); - yHiDHiDHiy_ge+=delta*(d_Hiy_i1*d_Hi_j1j2*d_Hiy_i2+d_Hiy_j1*d_Hi_i1j2*d_Hiy_i2); - } - } - } - - return; -} - - -void Calc_xHiDHiDHiy (const gsl_vector *eval, const gsl_matrix *Hi, const gsl_matrix *xHi, const gsl_matrix *Hiy, const size_t i1, const size_t j1, const size_t i2, const size_t j2, gsl_vector *xHiDHiDHiy_gg, gsl_vector *xHiDHiDHiy_ee, gsl_vector *xHiDHiDHiy_ge) -{ - gsl_vector_set_zero(xHiDHiDHiy_gg); - gsl_vector_set_zero(xHiDHiDHiy_ee); - gsl_vector_set_zero(xHiDHiDHiy_ge); - - size_t n_size=eval->size, d_size=Hiy->size1; - - double delta, d_Hiy_i, d_Hiy_j, d_Hi_i1i2, d_Hi_i1j2, d_Hi_j1i2, d_Hi_j1j2; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - gsl_vector_const_view xHi_col_i=gsl_matrix_const_column (xHi, k*d_size+i1); - gsl_vector_const_view xHi_col_j=gsl_matrix_const_column (xHi, k*d_size+j1); - - d_Hiy_i=gsl_matrix_get (Hiy, i2, k); - d_Hiy_j=gsl_matrix_get (Hiy, j2, k); - - d_Hi_i1i2=gsl_matrix_get (Hi, i1, k*d_size+i2); - d_Hi_i1j2=gsl_matrix_get (Hi, i1, k*d_size+j2); - d_Hi_j1i2=gsl_matrix_get (Hi, j1, k*d_size+i2); - d_Hi_j1j2=gsl_matrix_get (Hi, j1, k*d_size+j2); - - if (i1==j1) { - gsl_blas_daxpy (delta*delta*d_Hi_j1i2*d_Hiy_j, &xHi_col_i.vector, xHiDHiDHiy_gg); - gsl_blas_daxpy (d_Hi_j1i2*d_Hiy_j, &xHi_col_i.vector, xHiDHiDHiy_ee); - gsl_blas_daxpy (delta*d_Hi_j1i2*d_Hiy_j, &xHi_col_i.vector, xHiDHiDHiy_ge); - - if (i2!=j2) { - gsl_blas_daxpy (delta*delta*d_Hi_j1j2*d_Hiy_i, &xHi_col_i.vector, xHiDHiDHiy_gg); - gsl_blas_daxpy (d_Hi_j1j2*d_Hiy_i, &xHi_col_i.vector, xHiDHiDHiy_ee); - gsl_blas_daxpy (delta*d_Hi_j1j2*d_Hiy_i, &xHi_col_i.vector, xHiDHiDHiy_ge); - } - } else { - gsl_blas_daxpy (delta*delta*d_Hi_j1i2*d_Hiy_j, &xHi_col_i.vector, xHiDHiDHiy_gg); - gsl_blas_daxpy (d_Hi_j1i2*d_Hiy_j, &xHi_col_i.vector, xHiDHiDHiy_ee); - gsl_blas_daxpy (delta*d_Hi_j1i2*d_Hiy_j, &xHi_col_i.vector, xHiDHiDHiy_ge); - - gsl_blas_daxpy (delta*delta*d_Hi_i1i2*d_Hiy_j, &xHi_col_j.vector, xHiDHiDHiy_gg); - gsl_blas_daxpy (d_Hi_i1i2*d_Hiy_j, &xHi_col_j.vector, xHiDHiDHiy_ee); - gsl_blas_daxpy (delta*d_Hi_i1i2*d_Hiy_j, &xHi_col_j.vector, xHiDHiDHiy_ge); - - if (i2!=j2) { - gsl_blas_daxpy (delta*delta*d_Hi_j1j2*d_Hiy_i, &xHi_col_i.vector, xHiDHiDHiy_gg); - gsl_blas_daxpy (d_Hi_j1j2*d_Hiy_i, &xHi_col_i.vector, xHiDHiDHiy_ee); - gsl_blas_daxpy (delta*d_Hi_j1j2*d_Hiy_i, &xHi_col_i.vector, xHiDHiDHiy_ge); - - gsl_blas_daxpy (delta*delta*d_Hi_i1j2*d_Hiy_i, &xHi_col_j.vector, xHiDHiDHiy_gg); - gsl_blas_daxpy (d_Hi_i1j2*d_Hiy_i, &xHi_col_j.vector, xHiDHiDHiy_ee); - gsl_blas_daxpy (delta*d_Hi_i1j2*d_Hiy_i, &xHi_col_j.vector, xHiDHiDHiy_ge); - } - } - } - - return; -} - - -void Calc_xHiDHiDHix (const gsl_vector *eval, const gsl_matrix *Hi, const gsl_matrix *xHi, const size_t i1, const size_t j1, const size_t i2, const size_t j2, gsl_matrix *xHiDHiDHix_gg, gsl_matrix *xHiDHiDHix_ee, gsl_matrix *xHiDHiDHix_ge) -{ - gsl_matrix_set_zero(xHiDHiDHix_gg); - gsl_matrix_set_zero(xHiDHiDHix_ee); - gsl_matrix_set_zero(xHiDHiDHix_ge); - - size_t n_size=eval->size, d_size=Hi->size1, dc_size=xHi->size1; - - double delta, d_Hi_i1i2, d_Hi_i1j2, d_Hi_j1i2, d_Hi_j1j2; - - gsl_matrix *mat_dcdc=gsl_matrix_alloc (dc_size, dc_size); - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - gsl_vector_const_view xHi_col_i1=gsl_matrix_const_column (xHi, k*d_size+i1); - gsl_vector_const_view xHi_col_j1=gsl_matrix_const_column (xHi, k*d_size+j1); - gsl_vector_const_view xHi_col_i2=gsl_matrix_const_column (xHi, k*d_size+i2); - gsl_vector_const_view xHi_col_j2=gsl_matrix_const_column (xHi, k*d_size+j2); - - d_Hi_i1i2=gsl_matrix_get (Hi, i1, k*d_size+i2); - d_Hi_i1j2=gsl_matrix_get (Hi, i1, k*d_size+j2); - d_Hi_j1i2=gsl_matrix_get (Hi, j1, k*d_size+i2); - d_Hi_j1j2=gsl_matrix_get (Hi, j1, k*d_size+j2); - - if (i1==j1) { - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (d_Hi_j1i2, &xHi_col_i1.vector, &xHi_col_j2.vector, mat_dcdc); - - gsl_matrix_add(xHiDHiDHix_ee, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_ge, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_gg, mat_dcdc); - - if (i2!=j2) { - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (d_Hi_j1j2, &xHi_col_i1.vector, &xHi_col_i2.vector, mat_dcdc); - - gsl_matrix_add(xHiDHiDHix_ee, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_ge, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_gg, mat_dcdc); - } - } else { - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (d_Hi_j1i2, &xHi_col_i1.vector, &xHi_col_j2.vector, mat_dcdc); - - gsl_matrix_add(xHiDHiDHix_ee, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_ge, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_gg, mat_dcdc); - - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (d_Hi_i1i2, &xHi_col_j1.vector, &xHi_col_j2.vector, mat_dcdc); - - gsl_matrix_add(xHiDHiDHix_ee, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_ge, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_gg, mat_dcdc); - - if (i2!=j2) { - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (d_Hi_j1j2, &xHi_col_i1.vector, &xHi_col_i2.vector, mat_dcdc); - - gsl_matrix_add(xHiDHiDHix_ee, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_ge, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_gg, mat_dcdc); - - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (d_Hi_i1j2, &xHi_col_j1.vector, &xHi_col_i2.vector, mat_dcdc); - - gsl_matrix_add(xHiDHiDHix_ee, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_ge, mat_dcdc); - gsl_matrix_scale(mat_dcdc, delta); - gsl_matrix_add(xHiDHiDHix_gg, mat_dcdc); - } - } - } - - gsl_matrix_free(mat_dcdc); - - return; -} - - - -void Calc_traceHiD (const gsl_vector *eval, const gsl_matrix *Hi, const size_t i, const size_t j, double &tHiD_g, double &tHiD_e) -{ - tHiD_g=0.0; - tHiD_e=0.0; - - size_t n_size=eval->size, d_size=Hi->size1; - double delta, d; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - d=gsl_matrix_get (Hi, j, k*d_size+i); - - if (i==j) { - tHiD_g+=delta*d; - tHiD_e+=d; - } else { - tHiD_g+=delta*d*2.0; - tHiD_e+=d*2.0; - } - } - - return; -} - - -void Calc_traceHiDHiD (const gsl_vector *eval, const gsl_matrix *Hi, const size_t i1, const size_t j1, const size_t i2, const size_t j2, double &tHiDHiD_gg, double &tHiDHiD_ee, double &tHiDHiD_ge) -{ - tHiDHiD_gg=0.0; - tHiDHiD_ee=0.0; - tHiDHiD_ge=0.0; - - size_t n_size=eval->size, d_size=Hi->size1; - double delta, d_Hi_i1i2, d_Hi_i1j2, d_Hi_j1i2, d_Hi_j1j2; - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - d_Hi_i1i2=gsl_matrix_get (Hi, i1, k*d_size+i2); - d_Hi_i1j2=gsl_matrix_get (Hi, i1, k*d_size+j2); - d_Hi_j1i2=gsl_matrix_get (Hi, j1, k*d_size+i2); - d_Hi_j1j2=gsl_matrix_get (Hi, j1, k*d_size+j2); - - if (i1==j1) { - tHiDHiD_gg+=delta*delta*d_Hi_i1j2*d_Hi_j1i2; - tHiDHiD_ee+=d_Hi_i1j2*d_Hi_j1i2; - tHiDHiD_ge+=delta*d_Hi_i1j2*d_Hi_j1i2; - - if (i2!=j2) { - tHiDHiD_gg+=delta*delta*d_Hi_i1i2*d_Hi_j1j2; - tHiDHiD_ee+=d_Hi_i1i2*d_Hi_j1j2; - tHiDHiD_ge+=delta*d_Hi_i1i2*d_Hi_j1j2; - } - } else { - tHiDHiD_gg+=delta*delta*(d_Hi_i1j2*d_Hi_j1i2+d_Hi_j1j2*d_Hi_i1i2); - tHiDHiD_ee+=(d_Hi_i1j2*d_Hi_j1i2+d_Hi_j1j2*d_Hi_i1i2); - tHiDHiD_ge+=delta*(d_Hi_i1j2*d_Hi_j1i2+d_Hi_j1j2*d_Hi_i1i2); - - if (i2!=j2) { - tHiDHiD_gg+=delta*delta*(d_Hi_i1i2*d_Hi_j1j2+d_Hi_j1i2*d_Hi_i1j2); - tHiDHiD_ee+=(d_Hi_i1i2*d_Hi_j1j2+d_Hi_j1i2*d_Hi_i1j2); - tHiDHiD_ge+=delta*(d_Hi_i1i2*d_Hi_j1j2+d_Hi_j1i2*d_Hi_i1j2); - } - } - } - - return; -} - - -//trace(PD)=trace((Hi-HixQixHi)D)=trace(HiD)-trace(HixQixHiD) -void Calc_tracePD (const gsl_vector *eval, const gsl_matrix *Qi, const gsl_matrix *Hi, const gsl_matrix *xHiDHix_all_g, const gsl_matrix *xHiDHix_all_e, const size_t i, const size_t j, double &tPD_g, double &tPD_e) -{ - size_t dc_size=Qi->size1, d_size=Hi->size1; - size_t v=GetIndex(i, j, d_size); - - double d; - - //calculate the first part: trace(HiD) - Calc_traceHiD (eval, Hi, i, j, tPD_g, tPD_e); - - //calculate the second part: -trace(HixQixHiD) - for (size_t k=0; k<dc_size; k++) { - gsl_vector_const_view Qi_row=gsl_matrix_const_row (Qi, k); - gsl_vector_const_view xHiDHix_g_col=gsl_matrix_const_column (xHiDHix_all_g, v*dc_size+k); - gsl_vector_const_view xHiDHix_e_col=gsl_matrix_const_column (xHiDHix_all_e, v*dc_size+k); - - gsl_blas_ddot(&Qi_row.vector, &xHiDHix_g_col.vector, &d); - tPD_g-=d; - gsl_blas_ddot(&Qi_row.vector, &xHiDHix_e_col.vector, &d); - tPD_e-=d; - } - - return; -} - - - -//trace(PDPD)=trace((Hi-HixQixHi)D(Hi-HixQixHi)D) -//=trace(HiDHiD)-trace(HixQixHiDHiD)-trace(HiDHixQixHiD)+trace(HixQixHiDHixQixHiD) -void Calc_tracePDPD (const gsl_vector *eval, const gsl_matrix *Qi, const gsl_matrix *Hi, const gsl_matrix *xHi, const gsl_matrix *QixHiDHix_all_g, const gsl_matrix *QixHiDHix_all_e, const gsl_matrix *xHiDHiDHix_all_gg, const gsl_matrix *xHiDHiDHix_all_ee, const gsl_matrix *xHiDHiDHix_all_ge, const size_t i1, const size_t j1, const size_t i2, const size_t j2, double &tPDPD_gg, double &tPDPD_ee, double &tPDPD_ge) -{ - size_t dc_size=Qi->size1, d_size=Hi->size1; - size_t v_size=d_size*(d_size+1)/2; - size_t v1=GetIndex(i1, j1, d_size), v2=GetIndex(i2, j2, d_size); - - double d; - - //calculate the first part: trace(HiDHiD) - Calc_traceHiDHiD (eval, Hi, i1, j1, i2, j2, tPDPD_gg, tPDPD_ee, tPDPD_ge); - - //calculate the second and third parts: -trace(HixQixHiDHiD)-trace(HiDHixQixHiD) - for (size_t i=0; i<dc_size; i++) { - gsl_vector_const_view Qi_row=gsl_matrix_const_row (Qi, i); - gsl_vector_const_view xHiDHiDHix_gg_col=gsl_matrix_const_column (xHiDHiDHix_all_gg, (v1*v_size+v2)*dc_size+i); - gsl_vector_const_view xHiDHiDHix_ee_col=gsl_matrix_const_column (xHiDHiDHix_all_ee, (v1*v_size+v2)*dc_size+i); - gsl_vector_const_view xHiDHiDHix_ge_col=gsl_matrix_const_column (xHiDHiDHix_all_ge, (v1*v_size+v2)*dc_size+i); - - gsl_blas_ddot(&Qi_row.vector, &xHiDHiDHix_gg_col.vector, &d); - tPDPD_gg-=d*2.0; - gsl_blas_ddot(&Qi_row.vector, &xHiDHiDHix_ee_col.vector, &d); - tPDPD_ee-=d*2.0; - gsl_blas_ddot(&Qi_row.vector, &xHiDHiDHix_ge_col.vector, &d); - tPDPD_ge-=d*2.0; - /* - gsl_vector_const_view xHiDHiDHix_gg_row=gsl_matrix_const_row (xHiDHiDHix_gg, i); - gsl_vector_const_view xHiDHiDHix_ee_row=gsl_matrix_const_row (xHiDHiDHix_ee, i); - gsl_vector_const_view xHiDHiDHix_ge_row=gsl_matrix_const_row (xHiDHiDHix_ge, i); - - gsl_blas_ddot(&Qi_row.vector, &xHiDHiDHix_gg_row.vector, &d); - tPDPD_gg-=d; - gsl_blas_ddot(&Qi_row.vector, &xHiDHiDHix_ee_row.vector, &d); - tPDPD_ee-=d; - gsl_blas_ddot(&Qi_row.vector, &xHiDHiDHix_ge_row.vector, &d); - tPDPD_ge-=d; - */ - } - - //calculate the fourth part: trace(HixQixHiDHixQixHiD) - for (size_t i=0; i<dc_size; i++) { - //gsl_vector_const_view QixHiDHix_g_row1=gsl_matrix_const_subrow (QixHiDHix_all_g, i, v1*dc_size, dc_size); - //gsl_vector_const_view QixHiDHix_e_row1=gsl_matrix_const_subrow (QixHiDHix_all_e, i, v1*dc_size, dc_size); - - gsl_vector_const_view QixHiDHix_g_fullrow1=gsl_matrix_const_row (QixHiDHix_all_g, i); - gsl_vector_const_view QixHiDHix_e_fullrow1=gsl_matrix_const_row (QixHiDHix_all_e, i); - gsl_vector_const_view QixHiDHix_g_row1=gsl_vector_const_subvector (&QixHiDHix_g_fullrow1.vector, v1*dc_size, dc_size); - gsl_vector_const_view QixHiDHix_e_row1=gsl_vector_const_subvector (&QixHiDHix_e_fullrow1.vector, v1*dc_size, dc_size); - - gsl_vector_const_view QixHiDHix_g_col2=gsl_matrix_const_column (QixHiDHix_all_g, v2*dc_size+i); - gsl_vector_const_view QixHiDHix_e_col2=gsl_matrix_const_column (QixHiDHix_all_e, v2*dc_size+i); - - gsl_blas_ddot(&QixHiDHix_g_row1.vector, &QixHiDHix_g_col2.vector, &d); - tPDPD_gg+=d; - gsl_blas_ddot(&QixHiDHix_e_row1.vector, &QixHiDHix_e_col2.vector, &d); - tPDPD_ee+=d; - gsl_blas_ddot(&QixHiDHix_g_row1.vector, &QixHiDHix_e_col2.vector, &d); - tPDPD_ge+=d; - } - - return; -} - - - -//calculate (xHiDHiy) for every pair of i j -void Calc_xHiDHiy_all (const gsl_vector *eval, const gsl_matrix *xHi, const gsl_matrix *Hiy, gsl_matrix *xHiDHiy_all_g, gsl_matrix *xHiDHiy_all_e) -{ - gsl_matrix_set_zero(xHiDHiy_all_g); - gsl_matrix_set_zero(xHiDHiy_all_e); - - size_t d_size=Hiy->size1; - size_t v; - - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - if (j<i) {continue;} - v=GetIndex(i, j, d_size); - - gsl_vector_view xHiDHiy_g=gsl_matrix_column (xHiDHiy_all_g, v); - gsl_vector_view xHiDHiy_e=gsl_matrix_column (xHiDHiy_all_e, v); - - Calc_xHiDHiy (eval, xHi, Hiy, i, j, &xHiDHiy_g.vector, &xHiDHiy_e.vector); - } - } - return; -} - - -//calculate (xHiDHix) for every pair of i j -void Calc_xHiDHix_all (const gsl_vector *eval, const gsl_matrix *xHi, gsl_matrix *xHiDHix_all_g, gsl_matrix *xHiDHix_all_e) -{ - gsl_matrix_set_zero(xHiDHix_all_g); - gsl_matrix_set_zero(xHiDHix_all_e); - - size_t d_size=xHi->size2/eval->size, dc_size=xHi->size1; - size_t v; - - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - if (j<i) {continue;} - v=GetIndex(i, j, d_size); - - gsl_matrix_view xHiDHix_g=gsl_matrix_submatrix (xHiDHix_all_g, 0, v*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHix_e=gsl_matrix_submatrix (xHiDHix_all_e, 0, v*dc_size, dc_size, dc_size); - - Calc_xHiDHix (eval, xHi, i, j, &xHiDHix_g.matrix, &xHiDHix_e.matrix); - } - } - return; -} - - - -//calculate (xHiDHiy) for every pair of i j -void Calc_xHiDHiDHiy_all (const size_t v_size, const gsl_vector *eval, const gsl_matrix *Hi, const gsl_matrix *xHi, const gsl_matrix *Hiy, gsl_matrix *xHiDHiDHiy_all_gg, gsl_matrix *xHiDHiDHiy_all_ee, gsl_matrix *xHiDHiDHiy_all_ge) -{ - gsl_matrix_set_zero(xHiDHiDHiy_all_gg); - gsl_matrix_set_zero(xHiDHiDHiy_all_ee); - gsl_matrix_set_zero(xHiDHiDHiy_all_ge); - - size_t d_size=Hiy->size1; - size_t v1, v2; - - for (size_t i1=0; i1<d_size; i1++) { - for (size_t j1=0; j1<d_size; j1++) { - if (j1<i1) {continue;} - v1=GetIndex(i1, j1, d_size); - - for (size_t i2=0; i2<d_size; i2++) { - for (size_t j2=0; j2<d_size; j2++) { - if (j2<i2) {continue;} - v2=GetIndex(i2, j2, d_size); - - gsl_vector_view xHiDHiDHiy_gg=gsl_matrix_column (xHiDHiDHiy_all_gg, v1*v_size+v2); - gsl_vector_view xHiDHiDHiy_ee=gsl_matrix_column (xHiDHiDHiy_all_ee, v1*v_size+v2); - gsl_vector_view xHiDHiDHiy_ge=gsl_matrix_column (xHiDHiDHiy_all_ge, v1*v_size+v2); - - Calc_xHiDHiDHiy (eval, Hi, xHi, Hiy, i1, j1, i2, j2, &xHiDHiDHiy_gg.vector, &xHiDHiDHiy_ee.vector, &xHiDHiDHiy_ge.vector); - } - } - } - } - return; -} - - -//calculate (xHiDHix) for every pair of i j -void Calc_xHiDHiDHix_all (const size_t v_size, const gsl_vector *eval, const gsl_matrix *Hi, const gsl_matrix *xHi, gsl_matrix *xHiDHiDHix_all_gg, gsl_matrix *xHiDHiDHix_all_ee, gsl_matrix *xHiDHiDHix_all_ge) -{ - gsl_matrix_set_zero(xHiDHiDHix_all_gg); - gsl_matrix_set_zero(xHiDHiDHix_all_ee); - gsl_matrix_set_zero(xHiDHiDHix_all_ge); - - size_t d_size=xHi->size2/eval->size, dc_size=xHi->size1; - size_t v1, v2; - - for (size_t i1=0; i1<d_size; i1++) { - for (size_t j1=0; j1<d_size; j1++) { - if (j1<i1) {continue;} - v1=GetIndex(i1, j1, d_size); - - for (size_t i2=0; i2<d_size; i2++) { - for (size_t j2=0; j2<d_size; j2++) { - if (j2<i2) {continue;} - v2=GetIndex(i2, j2, d_size); - - if (v2<v1) {continue;} - - gsl_matrix_view xHiDHiDHix_gg1=gsl_matrix_submatrix (xHiDHiDHix_all_gg, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ee1=gsl_matrix_submatrix (xHiDHiDHix_all_ee, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ge1=gsl_matrix_submatrix (xHiDHiDHix_all_ge, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - - Calc_xHiDHiDHix (eval, Hi, xHi, i1, j1, i2, j2, &xHiDHiDHix_gg1.matrix, &xHiDHiDHix_ee1.matrix, &xHiDHiDHix_ge1.matrix); - - if (v2!=v1) { - gsl_matrix_view xHiDHiDHix_gg2=gsl_matrix_submatrix (xHiDHiDHix_all_gg, 0, (v2*v_size+v1)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ee2=gsl_matrix_submatrix (xHiDHiDHix_all_ee, 0, (v2*v_size+v1)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ge2=gsl_matrix_submatrix (xHiDHiDHix_all_ge, 0, (v2*v_size+v1)*dc_size, dc_size, dc_size); - - gsl_matrix_memcpy (&xHiDHiDHix_gg2.matrix, &xHiDHiDHix_gg1.matrix); - gsl_matrix_memcpy (&xHiDHiDHix_ee2.matrix, &xHiDHiDHix_ee1.matrix); - gsl_matrix_memcpy (&xHiDHiDHix_ge2.matrix, &xHiDHiDHix_ge1.matrix); - } - } - } - } - } - - - /* - size_t n_size=eval->size; - double delta, d_Hi_ij; - - gsl_matrix *mat_dcdc=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *mat_dcdc_temp=gsl_matrix_alloc (dc_size, dc_size); - - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get (eval, k); - - for (size_t i1=0; i1<d_size; i1++) { - for (size_t j2=0; j2<d_size; j2++) { - gsl_vector_const_view xHi_col_i=gsl_matrix_const_column (xHi, k*d_size+i1); - gsl_vector_const_view xHi_col_j=gsl_matrix_const_column (xHi, k*d_size+j2); - - gsl_matrix_set_zero (mat_dcdc); - gsl_blas_dger (1.0, &xHi_col_i.vector, &xHi_col_j.vector, mat_dcdc); - - for (size_t j1=0; j1<d_size; j1++) { - for (size_t i2=0; i2<d_size; i2++) { - d_Hi_ij=gsl_matrix_get (Hi, j1, k*d_size+i2); - - v1=GetIndex(i1, j1, d_size); - v2=GetIndex(i2, j2, d_size); - - gsl_matrix_view xHiDHiDHix_gg=gsl_matrix_submatrix (xHiDHiDHix_all_gg, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ee=gsl_matrix_submatrix (xHiDHiDHix_all_ee, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ge=gsl_matrix_submatrix (xHiDHiDHix_all_ge, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - - gsl_matrix_memcpy (mat_dcdc_temp, mat_dcdc); - - gsl_matrix_scale (mat_dcdc_temp, d_Hi_ij); - gsl_matrix_add(&xHiDHiDHix_ee.matrix, mat_dcdc_temp); - gsl_matrix_scale(mat_dcdc_temp, delta); - gsl_matrix_add(&xHiDHiDHix_ge.matrix, mat_dcdc_temp); - gsl_matrix_scale(mat_dcdc_temp, delta); - gsl_matrix_add(&xHiDHiDHix_gg.matrix, mat_dcdc_temp); - } - } - } - } - } - - for (size_t i1=0; i1<d_size; i1++) { - for (size_t j1=0; j1<d_size; j1++) { - v1=GetIndex(i1, j1, d_size); - - for (size_t i2=0; i2<d_size; i2++) { - for (size_t j2=0; j2<d_size; j2++) { - v2=GetIndex(i2, j2, d_size); - - if (i1!=j1 && i2!=j2) {continue;} - - gsl_matrix_view xHiDHiDHix_gg=gsl_matrix_submatrix (xHiDHiDHix_all_gg, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ee=gsl_matrix_submatrix (xHiDHiDHix_all_ee, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_view xHiDHiDHix_ge=gsl_matrix_submatrix (xHiDHiDHix_all_ge, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - - if ( (i1==j1 && i2!=j2) || (i1!=j1 && i2==j2) ) { - gsl_matrix_scale (&xHiDHiDHix_gg.matrix, 0.5); - gsl_matrix_scale (&xHiDHiDHix_ee.matrix, 0.5); - gsl_matrix_scale (&xHiDHiDHix_ge.matrix, 0.5); - } else { - gsl_matrix_scale (&xHiDHiDHix_gg.matrix, 0.25); - gsl_matrix_scale (&xHiDHiDHix_ee.matrix, 0.25); - gsl_matrix_scale (&xHiDHiDHix_ge.matrix, 0.25); - } - } - } - } - } - - gsl_matrix_free (mat_dcdc); - gsl_matrix_free (mat_dcdc_temp); - */ - - return; -} - - - -//calculate (xHiDHix)Qi(xHiy) for every pair of i, j -void Calc_xHiDHixQixHiy_all (const gsl_matrix *xHiDHix_all_g, const gsl_matrix *xHiDHix_all_e, const gsl_vector *QixHiy, gsl_matrix *xHiDHixQixHiy_all_g, gsl_matrix *xHiDHixQixHiy_all_e) -{ - size_t dc_size=xHiDHix_all_g->size1; - size_t v_size=xHiDHix_all_g->size2/dc_size; - - for (size_t i=0; i<v_size; i++) { - gsl_matrix_const_view xHiDHix_g=gsl_matrix_const_submatrix (xHiDHix_all_g, 0, i*dc_size, dc_size, dc_size); - gsl_matrix_const_view xHiDHix_e=gsl_matrix_const_submatrix (xHiDHix_all_e, 0, i*dc_size, dc_size, dc_size); - - gsl_vector_view xHiDHixQixHiy_g=gsl_matrix_column (xHiDHixQixHiy_all_g, i); - gsl_vector_view xHiDHixQixHiy_e=gsl_matrix_column (xHiDHixQixHiy_all_e, i); - - gsl_blas_dgemv (CblasNoTrans, 1.0, &xHiDHix_g.matrix, QixHiy, 0.0, &xHiDHixQixHiy_g.vector); - gsl_blas_dgemv (CblasNoTrans, 1.0, &xHiDHix_e.matrix, QixHiy, 0.0, &xHiDHixQixHiy_e.vector); - } - - return; -} - -//calculate Qi(xHiDHiy) and Qi(xHiDHix)Qi(xHiy) for each pair of i j (i<=j) -void Calc_QiVec_all (const gsl_matrix *Qi, const gsl_matrix *vec_all_g, const gsl_matrix *vec_all_e, gsl_matrix *Qivec_all_g, gsl_matrix *Qivec_all_e) -{ - for (size_t i=0; i<vec_all_g->size2; i++) { - gsl_vector_const_view vec_g=gsl_matrix_const_column (vec_all_g, i); - gsl_vector_const_view vec_e=gsl_matrix_const_column (vec_all_e, i); - - gsl_vector_view Qivec_g=gsl_matrix_column (Qivec_all_g, i); - gsl_vector_view Qivec_e=gsl_matrix_column (Qivec_all_e, i); - - gsl_blas_dgemv (CblasNoTrans, 1.0, Qi, &vec_g.vector, 0.0, &Qivec_g.vector); - gsl_blas_dgemv (CblasNoTrans, 1.0, Qi, &vec_e.vector, 0.0, &Qivec_e.vector); - } - - return; -} - - -//calculate Qi(xHiDHix) for each pair of i j (i<=j) -void Calc_QiMat_all (const gsl_matrix *Qi, const gsl_matrix *mat_all_g, const gsl_matrix *mat_all_e, gsl_matrix *Qimat_all_g, gsl_matrix *Qimat_all_e) -{ - size_t dc_size=Qi->size1; - size_t v_size=mat_all_g->size2/mat_all_g->size1; - - for (size_t i=0; i<v_size; i++) { - gsl_matrix_const_view mat_g=gsl_matrix_const_submatrix (mat_all_g, 0, i*dc_size, dc_size, dc_size); - gsl_matrix_const_view mat_e=gsl_matrix_const_submatrix (mat_all_e, 0, i*dc_size, dc_size, dc_size); - - gsl_matrix_view Qimat_g=gsl_matrix_submatrix (Qimat_all_g, 0, i*dc_size, dc_size, dc_size); - gsl_matrix_view Qimat_e=gsl_matrix_submatrix (Qimat_all_e, 0, i*dc_size, dc_size, dc_size); - - gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, Qi, &mat_g.matrix, 0.0, &Qimat_g.matrix); - gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, Qi, &mat_e.matrix, 0.0, &Qimat_e.matrix); - } - - return; -} - - - -//calculate yPDPy -//yPDPy=y(Hi-HixQixHi)D(Hi-HixQixHi)y -//=ytHiDHiy -//-(yHix)Qi(xHiDHiy)-(yHiDHix)Qi(xHiy) -//+(yHix)Qi(xHiDHix)Qi(xtHiy) -void Calc_yPDPy (const gsl_vector *eval, const gsl_matrix *Hiy, const gsl_vector *QixHiy, const gsl_matrix *xHiDHiy_all_g, const gsl_matrix *xHiDHiy_all_e, const gsl_matrix *xHiDHixQixHiy_all_g, const gsl_matrix *xHiDHixQixHiy_all_e, const size_t i, const size_t j, double &yPDPy_g, double &yPDPy_e) -{ - size_t d_size=Hiy->size1; - size_t v=GetIndex(i, j, d_size); - - double d; - - //first part: ytHiDHiy - Calc_yHiDHiy (eval, Hiy, i, j, yPDPy_g, yPDPy_e); - - //second and third parts: -(yHix)Qi(xHiDHiy)-(yHiDHix)Qi(xHiy) - gsl_vector_const_view xHiDHiy_g=gsl_matrix_const_column (xHiDHiy_all_g, v); - gsl_vector_const_view xHiDHiy_e=gsl_matrix_const_column (xHiDHiy_all_e, v); - - gsl_blas_ddot(QixHiy, &xHiDHiy_g.vector, &d); - yPDPy_g-=d*2.0; - gsl_blas_ddot(QixHiy, &xHiDHiy_e.vector, &d); - yPDPy_e-=d*2.0; - - //fourth part: +(yHix)Qi(xHiDHix)Qi(xHiy) - gsl_vector_const_view xHiDHixQixHiy_g=gsl_matrix_const_column (xHiDHixQixHiy_all_g, v); - gsl_vector_const_view xHiDHixQixHiy_e=gsl_matrix_const_column (xHiDHixQixHiy_all_e, v); - - gsl_blas_ddot(QixHiy, &xHiDHixQixHiy_g.vector, &d); - yPDPy_g+=d; - gsl_blas_ddot(QixHiy, &xHiDHixQixHiy_e.vector, &d); - yPDPy_e+=d; - - return; -} - -//calculate yPDPDPy=y(Hi-HixQixHi)D(Hi-HixQixHi)D(Hi-HixQixHi)y -//yPDPDPy=yHiDHiDHiy -//-(yHix)Qi(xHiDHiDHiy)-(yHiDHiDHix)Qi(xHiy) -//-(yHiDHix)Qi(xHiDHiy) -//+(yHix)Qi(xHiDHix)Qi(xHiDHiy)+(yHiDHix)Qi(xHiDHix)Qi(xHiy) -//+(yHix)Qi(xHiDHiDHix)Qi(xHiy) -//-(yHix)Qi(xHiDHix)Qi(xHiDHix)Qi(xHiy) -void Calc_yPDPDPy (const gsl_vector *eval, const gsl_matrix *Hi, const gsl_matrix *xHi, const gsl_matrix *Hiy, const gsl_vector *QixHiy, const gsl_matrix *xHiDHiy_all_g, const gsl_matrix *xHiDHiy_all_e, const gsl_matrix *QixHiDHiy_all_g, const gsl_matrix *QixHiDHiy_all_e, const gsl_matrix *xHiDHixQixHiy_all_g, const gsl_matrix *xHiDHixQixHiy_all_e, const gsl_matrix *QixHiDHixQixHiy_all_g, const gsl_matrix *QixHiDHixQixHiy_all_e, const gsl_matrix *xHiDHiDHiy_all_gg, const gsl_matrix *xHiDHiDHiy_all_ee, const gsl_matrix *xHiDHiDHiy_all_ge, const gsl_matrix *xHiDHiDHix_all_gg, const gsl_matrix *xHiDHiDHix_all_ee, const gsl_matrix *xHiDHiDHix_all_ge, const size_t i1, const size_t j1, const size_t i2, const size_t j2, double &yPDPDPy_gg, double &yPDPDPy_ee, double &yPDPDPy_ge) -{ - size_t d_size=Hi->size1, dc_size=xHi->size1; - size_t v1=GetIndex(i1, j1, d_size), v2=GetIndex(i2, j2, d_size); - size_t v_size=d_size*(d_size+1)/2; - - double d; - - gsl_vector *xHiDHiDHixQixHiy=gsl_vector_alloc (dc_size); - - //first part: yHiDHiDHiy - Calc_yHiDHiDHiy (eval, Hi, Hiy, i1, j1, i2, j2, yPDPDPy_gg, yPDPDPy_ee, yPDPDPy_ge); - - //second and third parts: -(yHix)Qi(xHiDHiDHiy)-(yHiDHiDHix)Qi(xHiy) - gsl_vector_const_view xHiDHiDHiy_gg1=gsl_matrix_const_column (xHiDHiDHiy_all_gg, v1*v_size+v2); - gsl_vector_const_view xHiDHiDHiy_ee1=gsl_matrix_const_column (xHiDHiDHiy_all_ee, v1*v_size+v2); - gsl_vector_const_view xHiDHiDHiy_ge1=gsl_matrix_const_column (xHiDHiDHiy_all_ge, v1*v_size+v2); - - gsl_vector_const_view xHiDHiDHiy_gg2=gsl_matrix_const_column (xHiDHiDHiy_all_gg, v2*v_size+v1); - gsl_vector_const_view xHiDHiDHiy_ee2=gsl_matrix_const_column (xHiDHiDHiy_all_ee, v2*v_size+v1); - gsl_vector_const_view xHiDHiDHiy_ge2=gsl_matrix_const_column (xHiDHiDHiy_all_ge, v2*v_size+v1); - - gsl_blas_ddot(QixHiy, &xHiDHiDHiy_gg1.vector, &d); - yPDPDPy_gg-=d; - gsl_blas_ddot(QixHiy, &xHiDHiDHiy_ee1.vector, &d); - yPDPDPy_ee-=d; - gsl_blas_ddot(QixHiy, &xHiDHiDHiy_ge1.vector, &d); - yPDPDPy_ge-=d; - - gsl_blas_ddot(QixHiy, &xHiDHiDHiy_gg2.vector, &d); - yPDPDPy_gg-=d; - gsl_blas_ddot(QixHiy, &xHiDHiDHiy_ee2.vector, &d); - yPDPDPy_ee-=d; - gsl_blas_ddot(QixHiy, &xHiDHiDHiy_ge2.vector, &d); - yPDPDPy_ge-=d; - - //fourth part: -(yHiDHix)Qi(xHiDHiy) - gsl_vector_const_view xHiDHiy_g1=gsl_matrix_const_column (xHiDHiy_all_g, v1); - gsl_vector_const_view xHiDHiy_e1=gsl_matrix_const_column (xHiDHiy_all_e, v1); - gsl_vector_const_view QixHiDHiy_g2=gsl_matrix_const_column (QixHiDHiy_all_g, v2); - gsl_vector_const_view QixHiDHiy_e2=gsl_matrix_const_column (QixHiDHiy_all_e, v2); - - gsl_blas_ddot(&xHiDHiy_g1.vector, &QixHiDHiy_g2.vector, &d); - yPDPDPy_gg-=d; - gsl_blas_ddot(&xHiDHiy_e1.vector, &QixHiDHiy_e2.vector, &d); - yPDPDPy_ee-=d; - gsl_blas_ddot(&xHiDHiy_g1.vector, &QixHiDHiy_e2.vector, &d); - yPDPDPy_ge-=d; - - //fifth and sixth parts: +(yHix)Qi(xHiDHix)Qi(xHiDHiy)+(yHiDHix)Qi(xHiDHix)Qi(xHiy) - gsl_vector_const_view QixHiDHiy_g1=gsl_matrix_const_column (QixHiDHiy_all_g, v1); - gsl_vector_const_view QixHiDHiy_e1=gsl_matrix_const_column (QixHiDHiy_all_e, v1); - - gsl_vector_const_view xHiDHixQixHiy_g1=gsl_matrix_const_column (xHiDHixQixHiy_all_g, v1); - gsl_vector_const_view xHiDHixQixHiy_e1=gsl_matrix_const_column (xHiDHixQixHiy_all_e, v1); - gsl_vector_const_view xHiDHixQixHiy_g2=gsl_matrix_const_column (xHiDHixQixHiy_all_g, v2); - gsl_vector_const_view xHiDHixQixHiy_e2=gsl_matrix_const_column (xHiDHixQixHiy_all_e, v2); - - gsl_blas_ddot(&xHiDHixQixHiy_g1.vector, &QixHiDHiy_g2.vector, &d); - yPDPDPy_gg+=d; - gsl_blas_ddot(&xHiDHixQixHiy_g2.vector, &QixHiDHiy_g1.vector, &d); - yPDPDPy_gg+=d; - - gsl_blas_ddot(&xHiDHixQixHiy_e1.vector, &QixHiDHiy_e2.vector, &d); - yPDPDPy_ee+=d; - gsl_blas_ddot(&xHiDHixQixHiy_e2.vector, &QixHiDHiy_e1.vector, &d); - yPDPDPy_ee+=d; - - gsl_blas_ddot(&xHiDHixQixHiy_g1.vector, &QixHiDHiy_e2.vector, &d); - yPDPDPy_ge+=d; - gsl_blas_ddot(&xHiDHixQixHiy_e2.vector, &QixHiDHiy_g1.vector, &d); - yPDPDPy_ge+=d; - - //seventh part: +(yHix)Qi(xHiDHiDHix)Qi(xHiy) - gsl_matrix_const_view xHiDHiDHix_gg=gsl_matrix_const_submatrix (xHiDHiDHix_all_gg, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_const_view xHiDHiDHix_ee=gsl_matrix_const_submatrix (xHiDHiDHix_all_ee, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_const_view xHiDHiDHix_ge=gsl_matrix_const_submatrix (xHiDHiDHix_all_ge, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - - gsl_blas_dgemv (CblasNoTrans, 1.0, &xHiDHiDHix_gg.matrix, QixHiy, 0.0, xHiDHiDHixQixHiy); - gsl_blas_ddot(xHiDHiDHixQixHiy, QixHiy, &d); - yPDPDPy_gg+=d; - gsl_blas_dgemv (CblasNoTrans, 1.0, &xHiDHiDHix_ee.matrix, QixHiy, 0.0, xHiDHiDHixQixHiy); - gsl_blas_ddot(xHiDHiDHixQixHiy, QixHiy, &d); - yPDPDPy_ee+=d; - gsl_blas_dgemv (CblasNoTrans, 1.0, &xHiDHiDHix_ge.matrix, QixHiy, 0.0, xHiDHiDHixQixHiy); - gsl_blas_ddot(xHiDHiDHixQixHiy, QixHiy, &d); - yPDPDPy_ge+=d; - - //eighth part: -(yHix)Qi(xHiDHix)Qi(xHiDHix)Qi(xHiy) - gsl_vector_const_view QixHiDHixQixHiy_g1=gsl_matrix_const_column (QixHiDHixQixHiy_all_g, v1); - gsl_vector_const_view QixHiDHixQixHiy_e1=gsl_matrix_const_column (QixHiDHixQixHiy_all_e, v1); - - gsl_blas_ddot(&QixHiDHixQixHiy_g1.vector, &xHiDHixQixHiy_g2.vector, &d); - yPDPDPy_gg-=d; - gsl_blas_ddot(&QixHiDHixQixHiy_e1.vector, &xHiDHixQixHiy_e2.vector, &d); - yPDPDPy_ee-=d; - gsl_blas_ddot(&QixHiDHixQixHiy_g1.vector, &xHiDHixQixHiy_e2.vector, &d); - yPDPDPy_ge-=d; - - //free memory - gsl_vector_free(xHiDHiDHixQixHiy); - - return; -} - - -//calculate Edgeworth correctation factors for small samples -//notation and method follows Thomas J. Rothenberg, Econometirca 1984; 52 (4) -//M=xHiDHix -void CalcCRT (const gsl_matrix *Hessian_inv, const gsl_matrix *Qi, const gsl_matrix *QixHiDHix_all_g, const gsl_matrix *QixHiDHix_all_e, const gsl_matrix *xHiDHiDHix_all_gg, const gsl_matrix *xHiDHiDHix_all_ee, const gsl_matrix *xHiDHiDHix_all_ge, const size_t d_size, double &crt_a, double &crt_b, double &crt_c) -{ - crt_a=0.0; crt_b=0.0; crt_c=0.0; - - size_t dc_size=Qi->size1, v_size=Hessian_inv->size1/2; - size_t c_size=dc_size/d_size; - double h_gg, h_ge, h_ee, d, B=0.0, C=0.0, D=0.0; - double trCg1, trCe1, trCg2, trCe2, trB_gg, trB_ge, trB_ee, trCC_gg, trCC_ge, trCC_ee, trD_gg=0.0, trD_ge=0.0, trD_ee=0.0; - - gsl_matrix *QiMQi_g1=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMQi_e1=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMQi_g2=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMQi_e2=gsl_matrix_alloc (dc_size, dc_size); - - gsl_matrix *QiMQisQisi_g1=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *QiMQisQisi_e1=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *QiMQisQisi_g2=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *QiMQisQisi_e2=gsl_matrix_alloc (d_size, d_size); - - gsl_matrix *QiMQiMQi_gg=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMQiMQi_ge=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMQiMQi_ee=gsl_matrix_alloc (dc_size, dc_size); - - gsl_matrix *QiMMQi_gg=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMMQi_ge=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *QiMMQi_ee=gsl_matrix_alloc (dc_size, dc_size); - - gsl_matrix *Qi_si=gsl_matrix_alloc (d_size, d_size); - - gsl_matrix *M_dd=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *M_dcdc=gsl_matrix_alloc (dc_size, dc_size); - - //invert Qi_sub to Qi_si - gsl_matrix *Qi_sub=gsl_matrix_alloc (d_size, d_size); - - gsl_matrix_const_view Qi_s=gsl_matrix_const_submatrix (Qi, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - - int sig; - gsl_permutation * pmt=gsl_permutation_alloc (d_size); - - gsl_matrix_memcpy (Qi_sub, &Qi_s.matrix); - LUDecomp (Qi_sub, pmt, &sig); - LUInvert (Qi_sub, pmt, Qi_si); - - gsl_permutation_free(pmt); - gsl_matrix_free(Qi_sub); - - //calculate correctation factors - for (size_t v1=0; v1<v_size; v1++) { - //calculate Qi(xHiDHix)Qi, and subpart of it - gsl_matrix_const_view QiM_g1=gsl_matrix_const_submatrix (QixHiDHix_all_g, 0, v1*dc_size, dc_size, dc_size); - gsl_matrix_const_view QiM_e1=gsl_matrix_const_submatrix (QixHiDHix_all_e, 0, v1*dc_size, dc_size, dc_size); - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_g1.matrix, Qi, 0.0, QiMQi_g1); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_e1.matrix, Qi, 0.0, QiMQi_e1); - - gsl_matrix_view QiMQi_g1_s=gsl_matrix_submatrix (QiMQi_g1, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - gsl_matrix_view QiMQi_e1_s=gsl_matrix_submatrix (QiMQi_e1, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - - /* - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<setprecision(6)<<gsl_matrix_get(&QiMQi_g1_s.matrix, i, j)<<"\t"; - } - cout<<endl; - } -*/ - //calculate trCg1 and trCe1 - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQi_g1_s.matrix, Qi_si, 0.0, QiMQisQisi_g1); - trCg1=0.0; - for (size_t k=0; k<d_size; k++) { - trCg1-=gsl_matrix_get (QiMQisQisi_g1, k, k); - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQi_e1_s.matrix, Qi_si, 0.0, QiMQisQisi_e1); - trCe1=0.0; - for (size_t k=0; k<d_size; k++) { - trCe1-=gsl_matrix_get (QiMQisQisi_e1, k, k); - } - /* - cout<<v1<<endl; - cout<<"trCg1 = "<<trCg1<<", trCe1 = "<<trCe1<<endl; - */ - for (size_t v2=0; v2<v_size; v2++) { - if (v2<v1) {continue;} - - //calculate Qi(xHiDHix)Qi, and subpart of it - gsl_matrix_const_view QiM_g2=gsl_matrix_const_submatrix (QixHiDHix_all_g, 0, v2*dc_size, dc_size, dc_size); - gsl_matrix_const_view QiM_e2=gsl_matrix_const_submatrix (QixHiDHix_all_e, 0, v2*dc_size, dc_size, dc_size); - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_g2.matrix, Qi, 0.0, QiMQi_g2); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_e2.matrix, Qi, 0.0, QiMQi_e2); - - gsl_matrix_view QiMQi_g2_s=gsl_matrix_submatrix (QiMQi_g2, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - gsl_matrix_view QiMQi_e2_s=gsl_matrix_submatrix (QiMQi_e2, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - - //calculate trCg2 and trCe2 - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQi_g2_s.matrix, Qi_si, 0.0, QiMQisQisi_g2); - trCg2=0.0; - for (size_t k=0; k<d_size; k++) { - trCg2-=gsl_matrix_get (QiMQisQisi_g2, k, k); - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQi_e2_s.matrix, Qi_si, 0.0, QiMQisQisi_e2); - trCe2=0.0; - for (size_t k=0; k<d_size; k++) { - trCe2-=gsl_matrix_get (QiMQisQisi_e2, k, k); - } - - //calculate trCC_gg, trCC_ge, trCC_ee - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, QiMQisQisi_g1, QiMQisQisi_g2, 0.0, M_dd); - trCC_gg=0.0; - for (size_t k=0; k<d_size; k++) { - trCC_gg+=gsl_matrix_get (M_dd, k, k); - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, QiMQisQisi_g1, QiMQisQisi_e2, 0.0, M_dd); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, QiMQisQisi_e1, QiMQisQisi_g2, 1.0, M_dd); - trCC_ge=0.0; - for (size_t k=0; k<d_size; k++) { - trCC_ge+=gsl_matrix_get (M_dd, k, k); - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, QiMQisQisi_e1, QiMQisQisi_e2, 0.0, M_dd); - trCC_ee=0.0; - for (size_t k=0; k<d_size; k++) { - trCC_ee+=gsl_matrix_get (M_dd, k, k); - } - - //calculate Qi(xHiDHix)Qi(xHiDHix)Qi, and subpart of it - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_g1.matrix, QiMQi_g2, 0.0, QiMQiMQi_gg); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_g1.matrix, QiMQi_e2, 0.0, QiMQiMQi_ge); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_e1.matrix, QiMQi_g2, 1.0, QiMQiMQi_ge); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiM_e1.matrix, QiMQi_e2, 0.0, QiMQiMQi_ee); - - gsl_matrix_view QiMQiMQi_gg_s=gsl_matrix_submatrix (QiMQiMQi_gg, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - gsl_matrix_view QiMQiMQi_ge_s=gsl_matrix_submatrix (QiMQiMQi_ge, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - gsl_matrix_view QiMQiMQi_ee_s=gsl_matrix_submatrix (QiMQiMQi_ee, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - - //and part of trB_gg, trB_ge, trB_ee - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQiMQi_gg_s.matrix, Qi_si, 0.0, M_dd); - trB_gg=0.0; - for (size_t k=0; k<d_size; k++) { - d=gsl_matrix_get (M_dd, k, k); - trB_gg-=d; - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQiMQi_ge_s.matrix, Qi_si, 0.0, M_dd); - trB_ge=0.0; - for (size_t k=0; k<d_size; k++) { - d=gsl_matrix_get (M_dd, k, k); - trB_ge-=d; - } - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMQiMQi_ee_s.matrix, Qi_si, 0.0, M_dd); - trB_ee=0.0; - for (size_t k=0; k<d_size; k++) { - d=gsl_matrix_get (M_dd, k, k); - trB_ee-=d; - } - - //calculate Qi(xHiDHiDHix)Qi, and subpart of it - gsl_matrix_const_view MM_gg=gsl_matrix_const_submatrix (xHiDHiDHix_all_gg, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_const_view MM_ge=gsl_matrix_const_submatrix (xHiDHiDHix_all_ge, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - gsl_matrix_const_view MM_ee=gsl_matrix_const_submatrix (xHiDHiDHix_all_ee, 0, (v1*v_size+v2)*dc_size, dc_size, dc_size); - - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Qi, &MM_gg.matrix, 0.0, M_dcdc); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, M_dcdc, Qi, 0.0, QiMMQi_gg); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Qi, &MM_ge.matrix, 0.0, M_dcdc); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, M_dcdc, Qi, 0.0, QiMMQi_ge); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, Qi, &MM_ee.matrix, 0.0, M_dcdc); - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, M_dcdc, Qi, 0.0, QiMMQi_ee); - - gsl_matrix_view QiMMQi_gg_s=gsl_matrix_submatrix (QiMMQi_gg, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - gsl_matrix_view QiMMQi_ge_s=gsl_matrix_submatrix (QiMMQi_ge, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - gsl_matrix_view QiMMQi_ee_s=gsl_matrix_submatrix (QiMMQi_ee, (c_size-1)*d_size, (c_size-1)*d_size, d_size, d_size); - - //calculate the other part of trB_gg, trB_ge, trB_ee - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMMQi_gg_s.matrix, Qi_si, 0.0, M_dd); - for (size_t k=0; k<d_size; k++) { - trB_gg+=gsl_matrix_get (M_dd, k, k); - } - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMMQi_ge_s.matrix, Qi_si, 0.0, M_dd); - for (size_t k=0; k<d_size; k++) { - trB_ge+=2.0*gsl_matrix_get (M_dd, k, k); - } - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, &QiMMQi_ee_s.matrix, Qi_si, 0.0, M_dd); - for (size_t k=0; k<d_size; k++) { - trB_ee+=gsl_matrix_get (M_dd, k, k); - } - - - //calculate trD_gg, trD_ge, trD_ee - trD_gg=2.0*trB_gg; - trD_ge=2.0*trB_ge; - trD_ee=2.0*trB_ee; - - //calculate B, C and D - h_gg=-1.0*gsl_matrix_get (Hessian_inv, v1, v2); - h_ge=-1.0*gsl_matrix_get (Hessian_inv, v1, v2+v_size); - h_ee=-1.0*gsl_matrix_get (Hessian_inv, v1+v_size, v2+v_size); - - B+=h_gg*trB_gg+h_ge*trB_ge+h_ee*trB_ee; - C+=h_gg*(trCC_gg+0.5*trCg1*trCg2)+h_ge*(trCC_ge+0.5*trCg1*trCe2+0.5*trCe1*trCg2)+h_ee*(trCC_ee+0.5*trCe1*trCe2); - D+=h_gg*(trCC_gg+0.5*trD_gg)+h_ge*(trCC_ge+0.5*trD_ge)+h_ee*(trCC_ee+0.5*trD_ee); - - if (v1!=v2) { - B+=h_gg*trB_gg+h_ge*trB_ge+h_ee*trB_ee; - C+=h_gg*(trCC_gg+0.5*trCg1*trCg2)+h_ge*(trCC_ge+0.5*trCg1*trCe2+0.5*trCe1*trCg2)+h_ee*(trCC_ee+0.5*trCe1*trCe2); - D+=h_gg*(trCC_gg+0.5*trD_gg)+h_ge*(trCC_ge+0.5*trD_ge)+h_ee*(trCC_ee+0.5*trD_ee); - } - - /* - cout<<v1<<"\t"<<v2<<endl; - cout<<h_gg<<"\t"<<h_ge<<"\t"<<h_ee<<endl; - cout<<trB_gg<<"\t"<<trB_ge<<"\t"<<trB_ee<<endl; - cout<<trCg1<<"\t"<<trCe1<<"\t"<<trCg2<<"\t"<<trCe2<<endl; - cout<<trCC_gg<<"\t"<<trCC_ge<<"\t"<<trCC_ee<<endl; - cout<<trD_gg<<"\t"<<trD_ge<<"\t"<<trD_ee<<endl; - */ - } - } - - //calculate a, b, c from B C D - crt_a=2.0*D-C; - crt_b=2.0*B; - crt_c=C; - /* - cout<<B<<"\t"<<C<<"\t"<<D<<endl; - cout<<setprecision(6)<<crt_a<<"\t"<<crt_b<<"\t"<<crt_c<<endl; - */ - //free matrix memory - gsl_matrix_free(QiMQi_g1); - gsl_matrix_free(QiMQi_e1); - gsl_matrix_free(QiMQi_g2); - gsl_matrix_free(QiMQi_e2); - - gsl_matrix_free(QiMQisQisi_g1); - gsl_matrix_free(QiMQisQisi_e1); - gsl_matrix_free(QiMQisQisi_g2); - gsl_matrix_free(QiMQisQisi_e2); - - gsl_matrix_free(QiMQiMQi_gg); - gsl_matrix_free(QiMQiMQi_ge); - gsl_matrix_free(QiMQiMQi_ee); - - gsl_matrix_free(QiMMQi_gg); - gsl_matrix_free(QiMMQi_ge); - gsl_matrix_free(QiMMQi_ee); - - gsl_matrix_free(Qi_si); - - gsl_matrix_free(M_dd); - gsl_matrix_free(M_dcdc); - - return; -} - - - - - -//calculate first-order and second-order derivatives -void CalcDev (const char func_name, const gsl_vector *eval, const gsl_matrix *Qi, const gsl_matrix *Hi, const gsl_matrix *xHi, const gsl_matrix *Hiy, const gsl_vector *QixHiy, gsl_vector *gradient, gsl_matrix *Hessian_inv, double &crt_a, double &crt_b, double &crt_c) -{ - if (func_name!='R' && func_name!='L' && func_name!='r' && func_name!='l') {cout<<"func_name only takes 'R' or 'L': 'R' for log-restricted likelihood, 'L' for log-likelihood."<<endl; return;} - - size_t dc_size=Qi->size1, d_size=Hi->size1; - size_t c_size=dc_size/d_size; - size_t v_size=d_size*(d_size+1)/2; - size_t v1, v2; - double dev1_g, dev1_e, dev2_gg, dev2_ee, dev2_ge; - - gsl_matrix *Hessian=gsl_matrix_alloc (v_size*2, v_size*2); - - gsl_matrix *xHiDHiy_all_g=gsl_matrix_alloc (dc_size, v_size); - gsl_matrix *xHiDHiy_all_e=gsl_matrix_alloc (dc_size, v_size); - gsl_matrix *xHiDHix_all_g=gsl_matrix_alloc (dc_size, v_size*dc_size); - gsl_matrix *xHiDHix_all_e=gsl_matrix_alloc (dc_size, v_size*dc_size); - gsl_matrix *xHiDHixQixHiy_all_g=gsl_matrix_alloc (dc_size, v_size); - gsl_matrix *xHiDHixQixHiy_all_e=gsl_matrix_alloc (dc_size, v_size); - - gsl_matrix *QixHiDHiy_all_g=gsl_matrix_alloc (dc_size, v_size); - gsl_matrix *QixHiDHiy_all_e=gsl_matrix_alloc (dc_size, v_size); - gsl_matrix *QixHiDHix_all_g=gsl_matrix_alloc (dc_size, v_size*dc_size); - gsl_matrix *QixHiDHix_all_e=gsl_matrix_alloc (dc_size, v_size*dc_size); - gsl_matrix *QixHiDHixQixHiy_all_g=gsl_matrix_alloc (dc_size, v_size); - gsl_matrix *QixHiDHixQixHiy_all_e=gsl_matrix_alloc (dc_size, v_size); - - gsl_matrix *xHiDHiDHiy_all_gg=gsl_matrix_alloc (dc_size, v_size*v_size); - gsl_matrix *xHiDHiDHiy_all_ee=gsl_matrix_alloc (dc_size, v_size*v_size); - gsl_matrix *xHiDHiDHiy_all_ge=gsl_matrix_alloc (dc_size, v_size*v_size); - gsl_matrix *xHiDHiDHix_all_gg=gsl_matrix_alloc (dc_size, v_size*v_size*dc_size); - gsl_matrix *xHiDHiDHix_all_ee=gsl_matrix_alloc (dc_size, v_size*v_size*dc_size); - gsl_matrix *xHiDHiDHix_all_ge=gsl_matrix_alloc (dc_size, v_size*v_size*dc_size); - - //calculate xHiDHiy_all, xHiDHix_all and xHiDHixQixHiy_all - Calc_xHiDHiy_all (eval, xHi, Hiy, xHiDHiy_all_g, xHiDHiy_all_e); - Calc_xHiDHix_all (eval, xHi, xHiDHix_all_g, xHiDHix_all_e); - Calc_xHiDHixQixHiy_all (xHiDHix_all_g, xHiDHix_all_e, QixHiy, xHiDHixQixHiy_all_g, xHiDHixQixHiy_all_e); - - Calc_xHiDHiDHiy_all (v_size, eval, Hi, xHi, Hiy, xHiDHiDHiy_all_gg, xHiDHiDHiy_all_ee, xHiDHiDHiy_all_ge); - Calc_xHiDHiDHix_all (v_size, eval, Hi, xHi, xHiDHiDHix_all_gg, xHiDHiDHix_all_ee, xHiDHiDHix_all_ge); - - //calculate QixHiDHiy_all, QixHiDHix_all and QixHiDHixQixHiy_all - Calc_QiVec_all (Qi, xHiDHiy_all_g, xHiDHiy_all_e, QixHiDHiy_all_g, QixHiDHiy_all_e); - Calc_QiVec_all (Qi, xHiDHixQixHiy_all_g, xHiDHixQixHiy_all_e, QixHiDHixQixHiy_all_g, QixHiDHixQixHiy_all_e); - Calc_QiMat_all (Qi, xHiDHix_all_g, xHiDHix_all_e, QixHiDHix_all_g, QixHiDHix_all_e); - - double tHiD_g, tHiD_e, tPD_g, tPD_e, tHiDHiD_gg, tHiDHiD_ee, tHiDHiD_ge, tPDPD_gg, tPDPD_ee, tPDPD_ge; - double yPDPy_g, yPDPy_e, yPDPDPy_gg, yPDPDPy_ee, yPDPDPy_ge; - - //calculate gradient and Hessian for Vg - for (size_t i1=0; i1<d_size; i1++) { - for (size_t j1=0; j1<d_size; j1++) { - if (j1<i1) {continue;} - v1=GetIndex (i1, j1, d_size); - - Calc_yPDPy (eval, Hiy, QixHiy, xHiDHiy_all_g, xHiDHiy_all_e, xHiDHixQixHiy_all_g, xHiDHixQixHiy_all_e, i1, j1, yPDPy_g, yPDPy_e); - - if (func_name=='R' || func_name=='r') { - Calc_tracePD (eval, Qi, Hi, xHiDHix_all_g, xHiDHix_all_e, i1, j1, tPD_g, tPD_e); - //cout<<i1<<" "<<j1<<" "<<yPDPy_g<<" "<<yPDPy_e<<" "<<tPD_g<<" "<<tPD_e<<endl; - - dev1_g=-0.5*tPD_g+0.5*yPDPy_g; - dev1_e=-0.5*tPD_e+0.5*yPDPy_e; - } else { - Calc_traceHiD (eval, Hi, i1, j1, tHiD_g, tHiD_e); - - dev1_g=-0.5*tHiD_g+0.5*yPDPy_g; - dev1_e=-0.5*tHiD_e+0.5*yPDPy_e; - } - - gsl_vector_set (gradient, v1, dev1_g); - gsl_vector_set (gradient, v1+v_size, dev1_e); - - for (size_t i2=0; i2<d_size; i2++) { - for (size_t j2=0; j2<d_size; j2++) { - if (j2<i2) {continue;} - v2=GetIndex (i2, j2, d_size); - - if (v2<v1) {continue;} - - Calc_yPDPDPy (eval, Hi, xHi, Hiy, QixHiy, xHiDHiy_all_g, xHiDHiy_all_e, QixHiDHiy_all_g, QixHiDHiy_all_e, xHiDHixQixHiy_all_g, xHiDHixQixHiy_all_e, QixHiDHixQixHiy_all_g, QixHiDHixQixHiy_all_e, xHiDHiDHiy_all_gg, xHiDHiDHiy_all_ee, xHiDHiDHiy_all_ge, xHiDHiDHix_all_gg, xHiDHiDHix_all_ee, xHiDHiDHix_all_ge, i1, j1, i2, j2, yPDPDPy_gg, yPDPDPy_ee, yPDPDPy_ge); - - //cout<<i1<<" "<<j1<<" "<<i2<<" "<<j2<<" "<<yPDPDPy_gg<<" "<<yPDPDPy_ee<<" "<<yPDPDPy_ge<<endl; - //AI for reml - if (func_name=='R' || func_name=='r') { - Calc_tracePDPD (eval, Qi, Hi, xHi, QixHiDHix_all_g, QixHiDHix_all_e, xHiDHiDHix_all_gg, xHiDHiDHix_all_ee, xHiDHiDHix_all_ge, i1, j1, i2, j2, tPDPD_gg, tPDPD_ee, tPDPD_ge); - - dev2_gg=0.5*tPDPD_gg-yPDPDPy_gg; - dev2_ee=0.5*tPDPD_ee-yPDPDPy_ee; - dev2_ge=0.5*tPDPD_ge-yPDPDPy_ge; - /* - dev2_gg=-0.5*yPDPDPy_gg; - dev2_ee=-0.5*yPDPDPy_ee; - dev2_ge=-0.5*yPDPDPy_ge; - */ - } else { - Calc_traceHiDHiD (eval, Hi, i1, j1, i2, j2, tHiDHiD_gg, tHiDHiD_ee, tHiDHiD_ge); - - dev2_gg=0.5*tHiDHiD_gg-yPDPDPy_gg; - dev2_ee=0.5*tHiDHiD_ee-yPDPDPy_ee; - dev2_ge=0.5*tHiDHiD_ge-yPDPDPy_ge; - } - - //set up Hessian - gsl_matrix_set (Hessian, v1, v2, dev2_gg); - gsl_matrix_set (Hessian, v1+v_size, v2+v_size, dev2_ee); - gsl_matrix_set (Hessian, v1, v2+v_size, dev2_ge); - gsl_matrix_set (Hessian, v2+v_size, v1, dev2_ge); - - if (v1!=v2) { - gsl_matrix_set (Hessian, v2, v1, dev2_gg); - gsl_matrix_set (Hessian, v2+v_size, v1+v_size, dev2_ee); - gsl_matrix_set (Hessian, v2, v1+v_size, dev2_ge); - gsl_matrix_set (Hessian, v1+v_size, v2, dev2_ge); - } - } - } - } - } - - /* - cout<<"Hessian: "<<endl; - for (size_t i=0; i<2*v_size; i++) { - for (size_t j=0; j<2*v_size; j++) { - cout<<gsl_matrix_get(Hessian, i, j)<<"\t"; - } - cout<<endl; - } - */ - - - //Invert Hessian - int sig; - gsl_permutation * pmt=gsl_permutation_alloc (v_size*2); - - LUDecomp (Hessian, pmt, &sig); - LUInvert (Hessian, pmt, Hessian_inv); - /* - cout<<"Hessian Inverse: "<<endl; - for (size_t i=0; i<2*v_size; i++) { - for (size_t j=0; j<2*v_size; j++) { - cout<<gsl_matrix_get(Hessian_inv, i, j)<<"\t"; - } - cout<<endl; - } - */ - gsl_permutation_free(pmt); - gsl_matrix_free(Hessian); - - //calculate Edgeworth correction factors - //after inverting Hessian - if (c_size>1) { - CalcCRT (Hessian_inv, Qi, QixHiDHix_all_g, QixHiDHix_all_e, xHiDHiDHix_all_gg, xHiDHiDHix_all_ee, xHiDHiDHix_all_ge, d_size, crt_a, crt_b, crt_c); - } else { - crt_a=0.0; crt_b=0.0; crt_c=0.0; - } - - gsl_matrix_free(xHiDHiy_all_g); - gsl_matrix_free(xHiDHiy_all_e); - gsl_matrix_free(xHiDHix_all_g); - gsl_matrix_free(xHiDHix_all_e); - gsl_matrix_free(xHiDHixQixHiy_all_g); - gsl_matrix_free(xHiDHixQixHiy_all_e); - - gsl_matrix_free(QixHiDHiy_all_g); - gsl_matrix_free(QixHiDHiy_all_e); - gsl_matrix_free(QixHiDHix_all_g); - gsl_matrix_free(QixHiDHix_all_e); - gsl_matrix_free(QixHiDHixQixHiy_all_g); - gsl_matrix_free(QixHiDHixQixHiy_all_e); - - gsl_matrix_free(xHiDHiDHiy_all_gg); - gsl_matrix_free(xHiDHiDHiy_all_ee); - gsl_matrix_free(xHiDHiDHiy_all_ge); - gsl_matrix_free(xHiDHiDHix_all_gg); - gsl_matrix_free(xHiDHiDHix_all_ee); - gsl_matrix_free(xHiDHiDHix_all_ge); - - return; -} - - -//update Vg, Ve -void UpdateVgVe (const gsl_matrix *Hessian_inv, const gsl_vector *gradient, const double step_scale, gsl_matrix *V_g, gsl_matrix *V_e) -{ - size_t v_size=gradient->size/2, d_size=V_g->size1; - size_t v; - - gsl_vector *vec_v=gsl_vector_alloc (v_size*2); - - double d; - - //vectorize Vg and Ve - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - if (j<i) {continue;} - v=GetIndex(i, j, d_size); - - d=gsl_matrix_get (V_g, i, j); - gsl_vector_set (vec_v, v, d); - - d=gsl_matrix_get (V_e, i, j); - gsl_vector_set (vec_v, v+v_size, d); - } - } - - gsl_blas_dgemv (CblasNoTrans, -1.0*step_scale, Hessian_inv, gradient, 1.0, vec_v); - - //save Vg and Ve - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - if (j<i) {continue;} - v=GetIndex(i, j, d_size); - - d=gsl_vector_get (vec_v, v); - gsl_matrix_set (V_g, i, j, d); - gsl_matrix_set (V_g, j, i, d); - - d=gsl_vector_get (vec_v, v+v_size); - gsl_matrix_set (V_e, i, j, d); - gsl_matrix_set (V_e, j, i, d); - } - } - - gsl_vector_free(vec_v); - - return; -} - - - - - - -double MphNR (const char func_name, const size_t max_iter, const double max_prec, const gsl_vector *eval, const gsl_matrix *X, const gsl_matrix *Y, gsl_matrix *Hi_all, gsl_matrix *xHi_all, gsl_matrix *Hiy_all, gsl_matrix *V_g, gsl_matrix *V_e, gsl_matrix *Hessian_inv, double &crt_a, double &crt_b, double &crt_c) -{ - if (func_name!='R' && func_name!='L' && func_name!='r' && func_name!='l') {cout<<"func_name only takes 'R' or 'L': 'R' for log-restricted likelihood, 'L' for log-likelihood."<<endl; return 0.0;} - size_t n_size=eval->size, c_size=X->size1, d_size=Y->size1; - size_t dc_size=d_size*c_size; - size_t v_size=d_size*(d_size+1)/2; - - double logdet_H, logdet_Q, yPy, logl_const, logl_old=0.0, logl_new=0.0, step_scale; - int sig; - size_t step_iter, flag_pd; - - gsl_matrix *Vg_save=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *Ve_save=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_temp=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *U_temp=gsl_matrix_alloc (d_size, d_size); - gsl_vector *D_temp=gsl_vector_alloc (d_size); - gsl_vector *xHiy=gsl_vector_alloc (dc_size); - gsl_vector *QixHiy=gsl_vector_alloc (dc_size); - gsl_matrix *Qi=gsl_matrix_alloc (dc_size, dc_size); - gsl_matrix *XXt=gsl_matrix_alloc (c_size, c_size); - - gsl_vector *gradient=gsl_vector_alloc (v_size*2); - - //calculate |XXt| and (XXt)^{-1} - gsl_blas_dsyrk (CblasUpper, CblasNoTrans, 1.0, X, 0.0, XXt); - for (size_t i=0; i<c_size; ++i) { - for (size_t j=0; j<i; ++j) { - gsl_matrix_set (XXt, i, j, gsl_matrix_get (XXt, j, i)); - } - } - - gsl_permutation * pmt=gsl_permutation_alloc (c_size); - LUDecomp (XXt, pmt, &sig); - gsl_permutation_free (pmt); -// LUInvert (XXt, pmt, XXti); - - //calculate the constant for logl - if (func_name=='R' || func_name=='r') { - logl_const=-0.5*(double)(n_size-c_size)*(double)d_size*log(2.0*M_PI)+0.5*(double)d_size*LULndet (XXt); - } else { - logl_const=-0.5*(double)n_size*(double)d_size*log(2.0*M_PI); - } - //optimization iterations - - for (size_t t=0; t<max_iter; t++) { - gsl_matrix_memcpy (Vg_save, V_g); - gsl_matrix_memcpy (Ve_save, V_e); - - step_scale=1.0; step_iter=0; - do { - gsl_matrix_memcpy (V_g, Vg_save); - gsl_matrix_memcpy (V_e, Ve_save); - - //update Vg, Ve, and invert Hessian - if (t!=0) {UpdateVgVe (Hessian_inv, gradient, step_scale, V_g, V_e);} - - //check if both Vg and Ve are positive definite - flag_pd=1; - gsl_matrix_memcpy (V_temp, V_e); - EigenDecomp(V_temp, U_temp, D_temp, 0); - for (size_t i=0; i<d_size; i++) { - if (gsl_vector_get (D_temp, i)<=0) {flag_pd=0;} - } - gsl_matrix_memcpy (V_temp, V_g); - EigenDecomp(V_temp, U_temp, D_temp, 0); - for (size_t i=0; i<d_size; i++) { - if (gsl_vector_get (D_temp, i)<=0) {flag_pd=0;} - } - - //if flag_pd==1 continue to calculate quantities and logl - if (flag_pd==1) { - CalcHiQi (eval, X, V_g, V_e, Hi_all, Qi, logdet_H, logdet_Q); - Calc_Hiy_all (Y, Hi_all, Hiy_all); - Calc_xHi_all (X, Hi_all, xHi_all); - - //calculate QixHiy and yPy - Calc_xHiy (Y, xHi_all, xHiy); - gsl_blas_dgemv (CblasNoTrans, 1.0, Qi, xHiy, 0.0, QixHiy); - - gsl_blas_ddot (QixHiy, xHiy, &yPy); - yPy=Calc_yHiy (Y, Hiy_all)-yPy; - - //calculate log likelihood/restricted likelihood value - if (func_name=='R' || func_name=='r') { - logl_new=logl_const-0.5*logdet_H-0.5*logdet_Q-0.5*yPy; - } else { - logl_new=logl_const-0.5*logdet_H-0.5*yPy; - } - } - - step_scale/=2.0; - step_iter++; - - //cout<<t<<"\t"<<step_iter<<"\t"<<logl_old<<"\t"<<logl_new<<"\t"<<flag_pd<<endl; - } while ( (flag_pd==0 || logl_new<logl_old || logl_new-logl_old>10 ) && step_iter<10 && t!=0); - - //terminate if change is small - if (t!=0) { - if (logl_new<logl_old || flag_pd==0) { - gsl_matrix_memcpy (V_g, Vg_save); - gsl_matrix_memcpy (V_e, Ve_save); - break; - } - - if (logl_new-logl_old<max_prec) { - break; - } - } - - logl_old=logl_new; - - CalcDev (func_name, eval, Qi, Hi_all, xHi_all, Hiy_all, QixHiy, gradient, Hessian_inv, crt_a, crt_b, crt_c); - - - //output estimates in each iteration - /* - cout<<func_name<<" iteration = "<<t<<" log-likelihood = "<<logl_old<<"\t"<<logl_new<<endl; - - cout<<"Vg: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get(V_g, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"Ve: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<d_size; j++) { - cout<<gsl_matrix_get(V_e, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"Hessian: "<<endl; - for (size_t i=0; i<Hessian_inv->size1; i++) { - for (size_t j=0; j<Hessian_inv->size2; j++) { - cout<<gsl_matrix_get(Hessian_inv, i, j)<<"\t"; - } - cout<<endl; - } - */ - } - - //mutiply Hessian_inv with -1.0 - //now Hessian_inv is the variance matrix - gsl_matrix_scale (Hessian_inv, -1.0); - - gsl_matrix_free(Vg_save); - gsl_matrix_free(Ve_save); - gsl_matrix_free(V_temp); - gsl_matrix_free(U_temp); - gsl_vector_free(D_temp); - gsl_vector_free(xHiy); - gsl_vector_free(QixHiy); - - gsl_matrix_free(Qi); - gsl_matrix_free(XXt); - - gsl_vector_free(gradient); - - return logl_new; -} - - - - - -//initialize Vg, Ve and B -void MphInitial(const size_t em_iter, const double em_prec, const size_t nr_iter, const double nr_prec, const gsl_vector *eval, const gsl_matrix *X, const gsl_matrix *Y, const double l_min, const double l_max, const size_t n_region, gsl_matrix *V_g, gsl_matrix *V_e, gsl_matrix *B) -{ - gsl_matrix_set_zero (V_g); - gsl_matrix_set_zero (V_e); - gsl_matrix_set_zero (B); - - size_t n_size=eval->size, c_size=X->size1, d_size=Y->size1; - double a, b, c; - double lambda, logl, vg, ve; - - //Initial the diagonal elements of Vg and Ve using univariate LMM and REML estimates - gsl_matrix *Xt=gsl_matrix_alloc (n_size, c_size); - gsl_vector *beta_temp=gsl_vector_alloc(c_size); - gsl_vector *se_beta_temp=gsl_vector_alloc(c_size); - - gsl_matrix_transpose_memcpy (Xt, X); - - for (size_t i=0; i<d_size; i++) { - gsl_vector_const_view Y_row=gsl_matrix_const_row (Y, i); - CalcLambda ('R', eval, Xt, &Y_row.vector, l_min, l_max, n_region, lambda, logl); - CalcLmmVgVeBeta (eval, Xt, &Y_row.vector, lambda, vg, ve, beta_temp, se_beta_temp); - - gsl_matrix_set(V_g, i, i, vg); - gsl_matrix_set(V_e, i, i, ve); - } - - gsl_matrix_free (Xt); - gsl_vector_free (beta_temp); - gsl_vector_free (se_beta_temp); - - //if number of phenotypes is above four, then obtain the off diagonal elements with two trait models - if (d_size>4) { - //first obtain good initial values - //large matrices for EM - gsl_matrix *U_hat=gsl_matrix_alloc (2, n_size); - gsl_matrix *E_hat=gsl_matrix_alloc (2, n_size); - gsl_matrix *OmegaU=gsl_matrix_alloc (2, n_size); - gsl_matrix *OmegaE=gsl_matrix_alloc (2, n_size); - gsl_matrix *UltVehiY=gsl_matrix_alloc (2, n_size); - gsl_matrix *UltVehiBX=gsl_matrix_alloc (2, n_size); - gsl_matrix *UltVehiU=gsl_matrix_alloc (2, n_size); - gsl_matrix *UltVehiE=gsl_matrix_alloc (2, n_size); - - //large matrices for NR - gsl_matrix *Hi_all=gsl_matrix_alloc (2, 2*n_size); //each dxd block is H_k^{-1} - gsl_matrix *Hiy_all=gsl_matrix_alloc (2, n_size); //each column is H_k^{-1}y_k - gsl_matrix *xHi_all=gsl_matrix_alloc (2*c_size, 2*n_size); //each dcxdc block is x_k\otimes H_k^{-1} - gsl_matrix *Hessian=gsl_matrix_alloc (6, 6); - - //2 by n matrix of Y - gsl_matrix *Y_sub=gsl_matrix_alloc (2, n_size); - gsl_matrix *Vg_sub=gsl_matrix_alloc (2, 2); - gsl_matrix *Ve_sub=gsl_matrix_alloc (2, 2); - gsl_matrix *B_sub=gsl_matrix_alloc (2, c_size); - - for (size_t i=0; i<d_size; i++) { - gsl_vector_view Y_sub1=gsl_matrix_row (Y_sub, 0); - gsl_vector_const_view Y_1=gsl_matrix_const_row (Y, i); - gsl_vector_memcpy (&Y_sub1.vector, &Y_1.vector); - - for (size_t j=i+1; j<d_size; j++) { - gsl_vector_view Y_sub2=gsl_matrix_row (Y_sub, 1); - gsl_vector_const_view Y_2=gsl_matrix_const_row (Y, j); - gsl_vector_memcpy (&Y_sub2.vector, &Y_2.vector); - - gsl_matrix_set_zero (Vg_sub); - gsl_matrix_set_zero (Ve_sub); - gsl_matrix_set (Vg_sub, 0, 0, gsl_matrix_get (V_g, i, i)); - gsl_matrix_set (Ve_sub, 0, 0, gsl_matrix_get (V_e, i, i)); - gsl_matrix_set (Vg_sub, 1, 1, gsl_matrix_get (V_g, j, j)); - gsl_matrix_set (Ve_sub, 1, 1, gsl_matrix_get (V_e, j, j)); - - logl=MphEM ('R', em_iter, em_prec, eval, X, Y_sub, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, Vg_sub, Ve_sub, B_sub); - logl=MphNR ('R', nr_iter, nr_prec, eval, X, Y_sub, Hi_all, xHi_all, Hiy_all, Vg_sub, Ve_sub, Hessian, a, b, c); - - gsl_matrix_set(V_g, i, j, gsl_matrix_get (Vg_sub, 0, 1)); - gsl_matrix_set(V_g, j, i, gsl_matrix_get (Vg_sub, 0, 1)); - - gsl_matrix_set(V_e, i, j, ve=gsl_matrix_get (Ve_sub, 0, 1)); - gsl_matrix_set(V_e, j, i, ve=gsl_matrix_get (Ve_sub, 0, 1)); - } - } - - //free matrices - gsl_matrix_free(U_hat); - gsl_matrix_free(E_hat); - gsl_matrix_free(OmegaU); - gsl_matrix_free(OmegaE); - gsl_matrix_free(UltVehiY); - gsl_matrix_free(UltVehiBX); - gsl_matrix_free(UltVehiU); - gsl_matrix_free(UltVehiE); - - gsl_matrix_free(Hi_all); - gsl_matrix_free(Hiy_all); - gsl_matrix_free(xHi_all); - gsl_matrix_free(Hessian); - - gsl_matrix_free(Y_sub); - gsl_matrix_free(Vg_sub); - gsl_matrix_free(Ve_sub); - gsl_matrix_free(B_sub); - - /* - //second, maximize a increasingly large matrix - for (size_t i=1; i<d_size; i++) { - //large matrices for EM - gsl_matrix *U_hat=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *E_hat=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *OmegaU=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *OmegaE=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *UltVehiY=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *UltVehiBX=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *UltVehiU=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *UltVehiE=gsl_matrix_alloc (i+1, n_size); - - //large matrices for NR - gsl_matrix *Hi_all=gsl_matrix_alloc (i+1, (i+1)*n_size); //each dxd block is H_k^{-1} - gsl_matrix *Hiy_all=gsl_matrix_alloc (i+1, n_size); //each column is H_k^{-1}y_k - gsl_matrix *xHi_all=gsl_matrix_alloc ((i+1)*c_size, (i+1)*n_size); //each dcxdc block is x_k\otimes H_k^{-1} - gsl_matrix *Hessian=gsl_matrix_alloc ((i+1)*(i+2), (i+1)*(i+2)); - - //(i+1) by n matrix of Y - gsl_matrix *Y_sub=gsl_matrix_alloc (i+1, n_size); - gsl_matrix *Vg_sub=gsl_matrix_alloc (i+1, i+1); - gsl_matrix *Ve_sub=gsl_matrix_alloc (i+1, i+1); - gsl_matrix *B_sub=gsl_matrix_alloc (i+1, c_size); - - gsl_matrix_const_view Y_sub_view=gsl_matrix_const_submatrix (Y, 0, 0, i+1, n_size); - gsl_matrix_view Vg_sub_view=gsl_matrix_submatrix (V_g, 0, 0, i+1, i+1); - gsl_matrix_view Ve_sub_view=gsl_matrix_submatrix (V_e, 0, 0, i+1, i+1); - - gsl_matrix_memcpy (Y_sub, &Y_sub_view.matrix); - gsl_matrix_memcpy (Vg_sub, &Vg_sub_view.matrix); - gsl_matrix_memcpy (Ve_sub, &Ve_sub_view.matrix); - - logl=MphEM ('R', em_iter, em_prec, eval, X, Y_sub, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, Vg_sub, Ve_sub, B_sub); - logl=MphNR ('R', nr_iter, nr_prec, eval, X, Y_sub, Hi_all, xHi_all, Hiy_all, Vg_sub, Ve_sub, Hessian, crt_a, crt_b, crt_c); - - gsl_matrix_memcpy (&Vg_sub_view.matrix, Vg_sub); - gsl_matrix_memcpy (&Ve_sub_view.matrix, Ve_sub); - - //free matrices - gsl_matrix_free(U_hat); - gsl_matrix_free(E_hat); - gsl_matrix_free(OmegaU); - gsl_matrix_free(OmegaE); - gsl_matrix_free(UltVehiY); - gsl_matrix_free(UltVehiBX); - gsl_matrix_free(UltVehiU); - gsl_matrix_free(UltVehiE); - - gsl_matrix_free(Hi_all); - gsl_matrix_free(Hiy_all); - gsl_matrix_free(xHi_all); - gsl_matrix_free(Hessian); - - gsl_matrix_free(Y_sub); - gsl_matrix_free(Vg_sub); - gsl_matrix_free(Ve_sub); - gsl_matrix_free(B_sub); - } - */ - } - - //calculate B hat using GSL estimate - gsl_matrix *UltVehiY=gsl_matrix_alloc (d_size, n_size); - - gsl_vector *D_l=gsl_vector_alloc (d_size); - gsl_matrix *UltVeh=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *UltVehi=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *Qi=gsl_matrix_alloc (d_size*c_size, d_size*c_size); - gsl_vector *XHiy=gsl_vector_alloc (d_size*c_size); - gsl_vector *beta=gsl_vector_alloc (d_size*c_size); - - gsl_vector_set_zero (XHiy); - - double logdet_Ve, logdet_Q, dl, d, delta, dx, dy; - - //eigen decomposition and calculate log|Ve| - logdet_Ve=EigenProc (V_g, V_e, D_l, UltVeh, UltVehi); - - //calculate Qi and log|Q| - logdet_Q=CalcQi (eval, D_l, X, Qi); - - //calculate UltVehiY - gsl_blas_dgemm(CblasNoTrans, CblasNoTrans, 1.0, UltVehi, Y, 0.0, UltVehiY); - - //calculate XHiy - for (size_t i=0; i<d_size; i++) { - dl=gsl_vector_get(D_l, i); - - for (size_t j=0; j<c_size; j++) { - d=0.0; - for (size_t k=0; k<n_size; k++) { - delta=gsl_vector_get(eval, k); - dx=gsl_matrix_get(X, j, k); - dy=gsl_matrix_get(UltVehiY, i, k); - - //if (delta==0) {continue;} - d+=dy*dx/(delta*dl+1.0); - } - gsl_vector_set(XHiy, j*d_size+i, d); - } - } - - gsl_blas_dgemv(CblasNoTrans, 1.0, Qi, XHiy, 0.0, beta); - - //multiply beta by UltVeh and save to B - for (size_t i=0; i<c_size; i++) { - gsl_vector_view B_col=gsl_matrix_column (B, i); - gsl_vector_view beta_sub=gsl_vector_subvector (beta, i*d_size, d_size); - gsl_blas_dgemv(CblasTrans, 1.0, UltVeh, &beta_sub.vector, 0.0, &B_col.vector); - } - - //free memory - gsl_matrix_free(UltVehiY); - - gsl_vector_free(D_l); - gsl_matrix_free(UltVeh); - gsl_matrix_free(UltVehi); - gsl_matrix_free(Qi); - gsl_vector_free(XHiy); - gsl_vector_free(beta); - - return; -} - - - -//p value correction -//mode=1 Wald; mode=2 LRT; mode=3 SCORE; -double PCRT (const size_t mode, const size_t d_size, const double p_value, const double crt_a, const double crt_b, const double crt_c) -{ - double p_crt=0.0, chisq_crt=0.0, q=(double)d_size; - double chisq=gsl_cdf_chisq_Qinv(p_value, (double)d_size ); - - if (mode==1) { - double a=crt_c/(2.0*q*(q+2.0)); - double b=1.0+(crt_a+crt_b)/(2.0*q); - chisq_crt=(-1.0*b+sqrt(b*b+4.0*a*chisq))/(2.0*a); - } else if (mode==2) { - chisq_crt=chisq/(1.0+crt_a/(2.0*q) ); - } else { - /* - double a=-1.0*crt_c/(2.0*q*(q+2.0)); - double b=1.0+(crt_a-crt_b)/(2.0*q); - chisq_crt=(-1.0*b+sqrt(b*b+4.0*a*chisq))/(2.0*a); - */ - chisq_crt=chisq; - } - - p_crt=gsl_cdf_chisq_Q (chisq_crt, (double)d_size ); - - //cout<<crt_a<<"\t"<<crt_b<<"\t"<<crt_c<<endl; - //cout<<setprecision(10)<<p_value<<"\t"<<p_crt<<endl; - - return p_crt; -} - - - -void MVLMM::AnalyzeBimbam (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_matrix *UtY) -{ - igzstream infile (file_geno.c_str(), igzstream::in); -// ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return;} - - clock_t time_start=clock(); - time_UtX=0; time_opt=0; - - string line; - char *ch_ptr; - - // double lambda_mle=0, lambda_remle=0, beta=0, se=0, ; - double logl_H0=0.0, logl_H1=0.0, p_wald=0, p_lrt=0, p_score=0; - double crt_a, crt_b, crt_c; - int n_miss, c_phen; - double geno, x_mean; - size_t c=0; - // double s=0.0; - size_t n_size=UtY->size1, d_size=UtY->size2, c_size=UtW->size2; - - size_t dc_size=d_size*(c_size+1), v_size=d_size*(d_size+1)/2; - - //large matrices for EM - gsl_matrix *U_hat=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *E_hat=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *OmegaU=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *OmegaE=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiY=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiBX=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiU=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiE=gsl_matrix_alloc (d_size, n_size); - - //large matrices for NR - gsl_matrix *Hi_all=gsl_matrix_alloc (d_size, d_size*n_size); //each dxd block is H_k^{-1} - gsl_matrix *Hiy_all=gsl_matrix_alloc (d_size, n_size); //each column is H_k^{-1}y_k - gsl_matrix *xHi_all=gsl_matrix_alloc (dc_size, d_size*n_size); //each dcxdc block is x_k\otimes H_k^{-1} - gsl_matrix *Hessian=gsl_matrix_alloc (v_size*2, v_size*2); - - gsl_vector *x=gsl_vector_alloc (n_size); - gsl_vector *x_miss=gsl_vector_alloc (n_size); - - gsl_matrix *Y=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *X=gsl_matrix_alloc (c_size+1, n_size); - gsl_matrix *V_g=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *B=gsl_matrix_alloc (d_size, c_size+1); - gsl_vector *beta=gsl_vector_alloc (d_size); - gsl_matrix *Vbeta=gsl_matrix_alloc (d_size, d_size); - - //null estimates for initial values - gsl_matrix *V_g_null=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e_null=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *B_null=gsl_matrix_alloc (d_size, c_size+1); - gsl_matrix *se_B_null=gsl_matrix_alloc (d_size, c_size); - - gsl_matrix_view X_sub=gsl_matrix_submatrix (X, 0, 0, c_size, n_size); - gsl_matrix_view B_sub=gsl_matrix_submatrix (B, 0, 0, d_size, c_size); - gsl_matrix_view xHi_all_sub=gsl_matrix_submatrix (xHi_all, 0, 0, d_size*c_size, d_size*n_size); - - gsl_matrix_transpose_memcpy (Y, UtY); - - gsl_matrix_transpose_memcpy (&X_sub.matrix, UtW); - - gsl_vector_view X_row=gsl_matrix_row(X, c_size); - gsl_vector_set_zero(&X_row.vector); - gsl_vector_view B_col=gsl_matrix_column(B, c_size); - gsl_vector_set_zero(&B_col.vector); - - MphInitial(em_iter, em_prec, nr_iter, nr_prec, eval, &X_sub.matrix, Y, l_min, l_max, n_region, V_g, V_e, &B_sub.matrix); - logl_H0=MphEM ('R', em_iter, em_prec, eval, &X_sub.matrix, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, &B_sub.matrix); - logl_H0=MphNR ('R', nr_iter, nr_prec, eval, &X_sub.matrix, Y, Hi_all, &xHi_all_sub.matrix, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - MphCalcBeta (eval, &X_sub.matrix, Y, V_g, V_e, UltVehiY, &B_sub.matrix, se_B_null); - - c=0; - Vg_remle_null.clear(); - Ve_remle_null.clear(); - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - Vg_remle_null.push_back(gsl_matrix_get (V_g, i, j) ); - Ve_remle_null.push_back(gsl_matrix_get (V_e, i, j) ); - VVg_remle_null.push_back(gsl_matrix_get (Hessian, c, c) ); - VVe_remle_null.push_back(gsl_matrix_get (Hessian, c+v_size, c+v_size) ); - c++; - } - } - beta_remle_null.clear(); - se_beta_remle_null.clear(); - for (size_t i=0; i<se_B_null->size1; i++) { - for (size_t j=0; j<se_B_null->size2; j++) { - beta_remle_null.push_back(gsl_matrix_get(B, i, j) ); - se_beta_remle_null.push_back(gsl_matrix_get(se_B_null, i, j) ); - } - } - logl_remle_H0=logl_H0; - - cout.setf(std::ios_base::fixed, std::ios_base::floatfield); - cout.precision(4); - - cout<<"REMLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_g, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Vg): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c, c))<<"\t"; - } - cout<<endl; - } - cout<<"REMLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_e, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Ve): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c+v_size, c+v_size))<<"\t"; - } - cout<<endl; - } - cout<<"REMLE likelihood = "<<logl_H0<<endl; - - - logl_H0=MphEM ('L', em_iter, em_prec, eval, &X_sub.matrix, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, &B_sub.matrix); - logl_H0=MphNR ('L', nr_iter, nr_prec, eval, &X_sub.matrix, Y, Hi_all, &xHi_all_sub.matrix, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - MphCalcBeta (eval, &X_sub.matrix, Y, V_g, V_e, UltVehiY, &B_sub.matrix, se_B_null); - - c=0; - Vg_mle_null.clear(); - Ve_mle_null.clear(); - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - Vg_mle_null.push_back(gsl_matrix_get (V_g, i, j) ); - Ve_mle_null.push_back(gsl_matrix_get (V_e, i, j) ); - VVg_mle_null.push_back(gsl_matrix_get (Hessian, c, c) ); - VVe_mle_null.push_back(gsl_matrix_get (Hessian, c+v_size, c+v_size) ); - c++; - } - } - beta_mle_null.clear(); - se_beta_mle_null.clear(); - for (size_t i=0; i<se_B_null->size1; i++) { - for (size_t j=0; j<se_B_null->size2; j++) { - beta_mle_null.push_back(gsl_matrix_get(B, i, j) ); - se_beta_mle_null.push_back(gsl_matrix_get(se_B_null, i, j) ); - } - } - logl_mle_H0=logl_H0; - - cout<<"MLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_g, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Vg): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c, c))<<"\t"; - } - cout<<endl; - } - cout<<"MLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_e, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Ve): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c+v_size, c+v_size))<<"\t"; - } - cout<<endl; - } - cout<<"MLE likelihood = "<<logl_H0<<endl; - - - vector<double> v_beta, v_Vg, v_Ve, v_Vbeta; - for (size_t i=0; i<d_size; i++) { - v_beta.push_back(0.0); - } - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - v_Vg.push_back(0.0); - v_Ve.push_back(0.0); - v_Vbeta.push_back(0.0); - } - } - - gsl_matrix_memcpy (V_g_null, V_g); - gsl_matrix_memcpy (V_e_null, V_e); - gsl_matrix_memcpy (B_null, B); - - //start reading genotypes and analyze - for (size_t t=0; t<indicator_snp.size(); ++t) { - //if (t>=1) {break;} - !safeGetline(infile, line).eof(); - if (t%d_pace==0 || t==(ns_total-1)) {ProgressBar ("Reading SNPs ", t, ns_total-1);} - if (indicator_snp[t]==0) {continue;} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - ch_ptr=strtok (NULL, " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - x_mean=0.0; c_phen=0; n_miss=0; - gsl_vector_set_zero(x_miss); - for (size_t i=0; i<ni_total; ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==0) {continue;} - - if (strcmp(ch_ptr, "NA")==0) {gsl_vector_set(x_miss, c_phen, 0.0); n_miss++;} - else { - geno=atof(ch_ptr); - - gsl_vector_set(x, c_phen, geno); - gsl_vector_set(x_miss, c_phen, 1.0); - x_mean+=geno; - } - c_phen++; - } - - x_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<ni_test; ++i) { - if (gsl_vector_get (x_miss, i)==0) {gsl_vector_set(x, i, x_mean);} - geno=gsl_vector_get(x, i); - if (x_mean>1) { - gsl_vector_set(x, i, 2-geno); - } - } - - //calculate statistics - time_start=clock(); - gsl_blas_dgemv (CblasTrans, 1.0, U, x, 0.0, &X_row.vector); - time_UtX+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //initial values - gsl_matrix_memcpy (V_g, V_g_null); - gsl_matrix_memcpy (V_e, V_e_null); - gsl_matrix_memcpy (B, B_null); - - time_start=clock(); - - //3 is before 1 - if (a_mode==3 || a_mode==4) { - p_score=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g_null, V_e_null, UltVehiY, beta, Vbeta); - if (p_score<p_nr && crt==1) { - logl_H1=MphNR ('R', 1, nr_prec*10, eval, X, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - p_score=PCRT (3, d_size, p_score, crt_a, crt_b, crt_c); - } - } - - if (a_mode==2 || a_mode==4) { - logl_H1=MphEM ('L', em_iter/10, em_prec*10, eval, X, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, B); - //calculate beta and Vbeta - p_lrt=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_H0), (double)d_size ); - - if (p_lrt<p_nr) { - logl_H1=MphNR ('L', nr_iter/10, nr_prec*10, eval, X, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - //calculate beta and Vbeta - p_lrt=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_H0), (double)d_size ); - - if (crt==1) { - p_lrt=PCRT (2, d_size, p_lrt, crt_a, crt_b, crt_c); - } - } - } - - if (a_mode==1 || a_mode==4) { - logl_H1=MphEM ('R', em_iter/10, em_prec*10, eval, X, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, B); - p_wald=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - - if (p_wald<p_nr) { - logl_H1=MphNR ('R', nr_iter/10, nr_prec*10, eval, X, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - p_wald=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - - if (crt==1) { - p_wald=PCRT (1, d_size, p_wald, crt_a, crt_b, crt_c); - } - } - } - - if (x_mean>1) {gsl_vector_scale(beta, -1.0);} - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - //SUMSTAT SNPs={snpInfo[t].get_chr(), snpInfo[t].get_rs(), snpInfo[t].get_pos(), n_miss, beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score}; - for (size_t i=0; i<d_size; i++) { - v_beta[i]=gsl_vector_get (beta, i); - } - - c=0; - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - v_Vg[c]=gsl_matrix_get (V_g, i, j); - v_Ve[c]=gsl_matrix_get (V_e, i, j); - v_Vbeta[c]=gsl_matrix_get (Vbeta, i, j); - c++; - } - } - - MPHSUMSTAT SNPs={v_beta, p_wald, p_lrt, p_score, v_Vg, v_Ve, v_Vbeta}; - sumStat.push_back(SNPs); - } - cout<<endl; - - - infile.close(); - infile.clear(); - - gsl_matrix_free(U_hat); - gsl_matrix_free(E_hat); - gsl_matrix_free(OmegaU); - gsl_matrix_free(OmegaE); - gsl_matrix_free(UltVehiY); - gsl_matrix_free(UltVehiBX); - gsl_matrix_free(UltVehiU); - gsl_matrix_free(UltVehiE); - - gsl_matrix_free(Hi_all); - gsl_matrix_free(Hiy_all); - gsl_matrix_free(xHi_all); - gsl_matrix_free(Hessian); - - gsl_vector_free(x); - gsl_vector_free(x_miss); - - gsl_matrix_free(Y); - gsl_matrix_free(X); - gsl_matrix_free(V_g); - gsl_matrix_free(V_e); - gsl_matrix_free(B); - gsl_vector_free(beta); - gsl_matrix_free(Vbeta); - - gsl_matrix_free(V_g_null); - gsl_matrix_free(V_e_null); - gsl_matrix_free(B_null); - gsl_matrix_free(se_B_null); - - return; -} - - - - - - - -void MVLMM::AnalyzePlink (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_matrix *UtY) -{ - string file_bed=file_bfile+".bed"; - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return;} - - clock_t time_start=clock(); - time_UtX=0; time_opt=0; - - char ch[1]; - bitset<8> b; - - // double lambda_mle=0, lambda_remle=0, beta=0, se=0, ; - double logl_H0=0.0, logl_H1=0.0, p_wald=0, p_lrt=0, p_score=0; - double crt_a, crt_b, crt_c; - int n_bit, n_miss, ci_total, ci_test; - double geno, x_mean; - size_t c=0; - // double s=0.0; - size_t n_size=UtY->size1, d_size=UtY->size2, c_size=UtW->size2; - size_t dc_size=d_size*(c_size+1), v_size=d_size*(d_size+1)/2; - - //large matrices for EM - gsl_matrix *U_hat=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *E_hat=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *OmegaU=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *OmegaE=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiY=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiBX=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiU=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiE=gsl_matrix_alloc (d_size, n_size); - - //large matrices for NR - gsl_matrix *Hi_all=gsl_matrix_alloc (d_size, d_size*n_size); //each dxd block is H_k^{-1} - gsl_matrix *Hiy_all=gsl_matrix_alloc (d_size, n_size); //each column is H_k^{-1}y_k - gsl_matrix *xHi_all=gsl_matrix_alloc (dc_size, d_size*n_size); //each dcxdc block is x_k\otimes H_k^{-1} - gsl_matrix *Hessian=gsl_matrix_alloc (v_size*2, v_size*2); - - gsl_vector *x=gsl_vector_alloc (n_size); - - gsl_matrix *Y=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *X=gsl_matrix_alloc (c_size+1, n_size); - gsl_matrix *V_g=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *B=gsl_matrix_alloc (d_size, c_size+1); - gsl_vector *beta=gsl_vector_alloc (d_size); - gsl_matrix *Vbeta=gsl_matrix_alloc (d_size, d_size); - - //null estimates for initial values - gsl_matrix *V_g_null=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *V_e_null=gsl_matrix_alloc (d_size, d_size); - gsl_matrix *B_null=gsl_matrix_alloc (d_size, c_size+1); - gsl_matrix *se_B_null=gsl_matrix_alloc (d_size, c_size); - - gsl_matrix_view X_sub=gsl_matrix_submatrix (X, 0, 0, c_size, n_size); - gsl_matrix_view B_sub=gsl_matrix_submatrix (B, 0, 0, d_size, c_size); - gsl_matrix_view xHi_all_sub=gsl_matrix_submatrix (xHi_all, 0, 0, d_size*c_size, d_size*n_size); - - gsl_matrix_transpose_memcpy (Y, UtY); - gsl_matrix_transpose_memcpy (&X_sub.matrix, UtW); - - gsl_vector_view X_row=gsl_matrix_row(X, c_size); - gsl_vector_set_zero(&X_row.vector); - gsl_vector_view B_col=gsl_matrix_column(B, c_size); - gsl_vector_set_zero(&B_col.vector); - - //time_start=clock(); - MphInitial(em_iter, em_prec, nr_iter, nr_prec, eval, &X_sub.matrix, Y, l_min, l_max, n_region, V_g, V_e, &B_sub.matrix); - - logl_H0=MphEM ('R', em_iter, em_prec, eval, &X_sub.matrix, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, &B_sub.matrix); - logl_H0=MphNR ('R', nr_iter, nr_prec, eval, &X_sub.matrix, Y, Hi_all, &xHi_all_sub.matrix, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - MphCalcBeta (eval, &X_sub.matrix, Y, V_g, V_e, UltVehiY, &B_sub.matrix, se_B_null); - //cout<<"time for REML in the null = "<<(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0)<<endl; - - c=0; - Vg_remle_null.clear(); - Ve_remle_null.clear(); - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - Vg_remle_null.push_back(gsl_matrix_get (V_g, i, j) ); - Ve_remle_null.push_back(gsl_matrix_get (V_e, i, j) ); - VVg_remle_null.push_back(gsl_matrix_get (Hessian, c, c) ); - VVe_remle_null.push_back(gsl_matrix_get (Hessian, c+v_size, c+v_size) ); - c++; - } - } - beta_remle_null.clear(); - se_beta_remle_null.clear(); - for (size_t i=0; i<se_B_null->size1; i++) { - for (size_t j=0; j<se_B_null->size2; j++) { - beta_remle_null.push_back(gsl_matrix_get(B, i, j) ); - se_beta_remle_null.push_back(gsl_matrix_get(se_B_null, i, j) ); - } - } - logl_remle_H0=logl_H0; - - cout.setf(std::ios_base::fixed, std::ios_base::floatfield); - cout.precision(4); - cout<<"REMLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_g, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Vg): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c, c))<<"\t"; - } - cout<<endl; - } - cout<<"REMLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_e, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Ve): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c+v_size, c+v_size))<<"\t"; - } - cout<<endl; - } - cout<<"REMLE likelihood = "<<logl_H0<<endl; - - //time_start=clock(); - logl_H0=MphEM ('L', em_iter, em_prec, eval, &X_sub.matrix, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, &B_sub.matrix); - logl_H0=MphNR ('L', nr_iter, nr_prec, eval, &X_sub.matrix, Y, Hi_all, &xHi_all_sub.matrix, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - MphCalcBeta (eval, &X_sub.matrix, Y, V_g, V_e, UltVehiY, &B_sub.matrix, se_B_null); - //cout<<"time for MLE in the null = "<<(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0)<<endl; - - c=0; - Vg_mle_null.clear(); - Ve_mle_null.clear(); - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - Vg_mle_null.push_back(gsl_matrix_get (V_g, i, j) ); - Ve_mle_null.push_back(gsl_matrix_get (V_e, i, j) ); - VVg_mle_null.push_back(gsl_matrix_get (Hessian, c, c) ); - VVe_mle_null.push_back(gsl_matrix_get (Hessian, c+v_size, c+v_size) ); - c++; - } - } - beta_mle_null.clear(); - se_beta_mle_null.clear(); - for (size_t i=0; i<se_B_null->size1; i++) { - for (size_t j=0; j<se_B_null->size2; j++) { - beta_mle_null.push_back(gsl_matrix_get(B, i, j) ); - se_beta_mle_null.push_back(gsl_matrix_get(se_B_null, i, j) ); - } - } - logl_mle_H0=logl_H0; - - cout<<"MLE estimate for Vg in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_g, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Vg): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c, c))<<"\t"; - } - cout<<endl; - } - cout<<"MLE estimate for Ve in the null model: "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - cout<<gsl_matrix_get(V_e, i, j)<<"\t"; - } - cout<<endl; - } - cout<<"se(Ve): "<<endl; - for (size_t i=0; i<d_size; i++) { - for (size_t j=0; j<=i; j++) { - c=GetIndex(i, j, d_size); - cout<<sqrt(gsl_matrix_get(Hessian, c+v_size, c+v_size))<<"\t"; - } - cout<<endl; - } - cout<<"MLE likelihood = "<<logl_H0<<endl; - - vector<double> v_beta, v_Vg, v_Ve, v_Vbeta; - for (size_t i=0; i<d_size; i++) { - v_beta.push_back(0.0); - } - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - v_Vg.push_back(0.0); - v_Ve.push_back(0.0); - v_Vbeta.push_back(0.0); - } - } - - gsl_matrix_memcpy (V_g_null, V_g); - gsl_matrix_memcpy (V_e_null, V_e); - gsl_matrix_memcpy (B_null, B); - - - //start reading genotypes and analyze - - //calculate n_bit and c, the number of bit for each snp - if (ni_total%4==0) {n_bit=ni_total/4;} - else {n_bit=ni_total/4+1; } - - //print the first three majic numbers - for (int i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - for (vector<SNPINFO>::size_type t=0; t<snpInfo.size(); ++t) { - if (t%d_pace==0 || t==snpInfo.size()-1) {ProgressBar ("Reading SNPs ", t, snpInfo.size()-1);} - if (indicator_snp[t]==0) {continue;} - - //if (t>=0) {break;} - //if (snpInfo[t].rs_number!="MAG18140902") {continue;} - //cout<<t<<endl; - - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - //read genotypes - x_mean=0.0; n_miss=0; ci_total=0; ci_test=0; - for (int i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && ci_total==(int)ni_total) {break;} - if (indicator_idv[ci_total]==0) {ci_total++; continue;} - - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(x, ci_test, 2); x_mean+=2.0; } - else {gsl_vector_set(x, ci_test, 1); x_mean+=1.0; } - } - else { - if (b[2*j+1]==1) {gsl_vector_set(x, ci_test, 0); } - else {gsl_vector_set(x, ci_test, -9); n_miss++; } - } - - ci_total++; - ci_test++; - } - } - - x_mean/=(double)(ni_test-n_miss); - - for (size_t i=0; i<ni_test; ++i) { - geno=gsl_vector_get(x,i); - if (geno==-9) {gsl_vector_set(x, i, x_mean); geno=x_mean;} - if (x_mean>1) { - gsl_vector_set(x, i, 2-geno); - } - } - - /* - if (t==0) { - ofstream outfile ("./snp1.txt", ofstream::out); - if (!outfile) {cout<<"error writing file: "<<endl; return;} - for (size_t i=0; i<x->size; i++) { - outfile<<gsl_vector_get(x, i)<<endl; - } - outfile.clear(); - outfile.close(); - } - */ - - //calculate statistics - time_start=clock(); - gsl_blas_dgemv (CblasTrans, 1.0, U, x, 0.0, &X_row.vector); - time_UtX+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //initial values - gsl_matrix_memcpy (V_g, V_g_null); - gsl_matrix_memcpy (V_e, V_e_null); - gsl_matrix_memcpy (B, B_null); - - time_start=clock(); - - //3 is before 1 - if (a_mode==3 || a_mode==4) { - p_score=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g_null, V_e_null, UltVehiY, beta, Vbeta); - - if (p_score<p_nr && crt==1) { - logl_H1=MphNR ('R', 1, nr_prec*10, eval, X, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - p_score=PCRT (3, d_size, p_score, crt_a, crt_b, crt_c); - } - } - - if (a_mode==2 || a_mode==4) { - logl_H1=MphEM ('L', em_iter/10, em_prec*10, eval, X, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, B); - //calculate beta and Vbeta - p_lrt=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_H0), (double)d_size ); - - if (p_lrt<p_nr) { - logl_H1=MphNR ('L', nr_iter/10, nr_prec*10, eval, X, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - - //calculate beta and Vbeta - p_lrt=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - p_lrt=gsl_cdf_chisq_Q (2.0*(logl_H1-logl_H0), (double)d_size ); - if (crt==1) { - p_lrt=PCRT (2, d_size, p_lrt, crt_a, crt_b, crt_c); - } - } - } - - if (a_mode==1 || a_mode==4) { - logl_H1=MphEM ('R', em_iter/10, em_prec*10, eval, X, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, B); - p_wald=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - - if (p_wald<p_nr) { - logl_H1=MphNR ('R', nr_iter/10, nr_prec*10, eval, X, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - p_wald=MphCalcP (eval, &X_row.vector, &X_sub.matrix, Y, V_g, V_e, UltVehiY, beta, Vbeta); - - if (crt==1) { - p_wald=PCRT (1, d_size, p_wald, crt_a, crt_b, crt_c); - } - } - } - - //cout<<setprecision(10)<<p_wald<<"\t"<<p_lrt<<"\t"<<p_score<<endl; - - if (x_mean>1) {gsl_vector_scale(beta, -1.0);} - - time_opt+=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - //store summary data - //SUMSTAT SNPs={snpInfo[t].get_chr(), snpInfo[t].get_rs(), snpInfo[t].get_pos(), n_miss, beta, se, lambda_remle, lambda_mle, p_wald, p_lrt, p_score}; - for (size_t i=0; i<d_size; i++) { - v_beta[i]=gsl_vector_get (beta, i); - } - - c=0; - for (size_t i=0; i<d_size; i++) { - for (size_t j=i; j<d_size; j++) { - v_Vg[c]=gsl_matrix_get (V_g, i, j); - v_Ve[c]=gsl_matrix_get (V_e, i, j); - v_Vbeta[c]=gsl_matrix_get (Vbeta, i, j); - c++; - } - } - - MPHSUMSTAT SNPs={v_beta, p_wald, p_lrt, p_score, v_Vg, v_Ve, v_Vbeta}; - sumStat.push_back(SNPs); - } - cout<<endl; - - //cout<<"time_opt = "<<time_opt<<endl; - - infile.close(); - infile.clear(); - - gsl_matrix_free(U_hat); - gsl_matrix_free(E_hat); - gsl_matrix_free(OmegaU); - gsl_matrix_free(OmegaE); - gsl_matrix_free(UltVehiY); - gsl_matrix_free(UltVehiBX); - gsl_matrix_free(UltVehiU); - gsl_matrix_free(UltVehiE); - - gsl_matrix_free(Hi_all); - gsl_matrix_free(Hiy_all); - gsl_matrix_free(xHi_all); - gsl_matrix_free(Hessian); - - gsl_vector_free(x); - - gsl_matrix_free(Y); - gsl_matrix_free(X); - gsl_matrix_free(V_g); - gsl_matrix_free(V_e); - gsl_matrix_free(B); - gsl_vector_free(beta); - gsl_matrix_free(Vbeta); - - gsl_matrix_free(V_g_null); - gsl_matrix_free(V_e_null); - gsl_matrix_free(B_null); - gsl_matrix_free(se_B_null); - - return; -} - - - - -//calculate Vg, Ve, B, se(B) in the null mvLMM model -//both B and se_B are d by c matrices -void CalcMvLmmVgVeBeta (const gsl_vector *eval, const gsl_matrix *UtW, const gsl_matrix *UtY, const size_t em_iter, const size_t nr_iter, const double em_prec, const double nr_prec, const double l_min, const double l_max, const size_t n_region, gsl_matrix *V_g, gsl_matrix *V_e, gsl_matrix *B, gsl_matrix *se_B) -{ - size_t n_size=UtY->size1, d_size=UtY->size2, c_size=UtW->size2; - size_t dc_size=d_size*c_size, v_size=d_size*(d_size+1)/2; - - double logl, crt_a, crt_b, crt_c; - - //large matrices for EM - gsl_matrix *U_hat=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *E_hat=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *OmegaU=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *OmegaE=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiY=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiBX=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiU=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *UltVehiE=gsl_matrix_alloc (d_size, n_size); - - //large matrices for NR - gsl_matrix *Hi_all=gsl_matrix_alloc (d_size, d_size*n_size); //each dxd block is H_k^{-1} - gsl_matrix *Hiy_all=gsl_matrix_alloc (d_size, n_size); //each column is H_k^{-1}y_k - gsl_matrix *xHi_all=gsl_matrix_alloc (dc_size, d_size*n_size); //each dcxdc block is x_k\otimes H_k^{-1} - gsl_matrix *Hessian=gsl_matrix_alloc (v_size*2, v_size*2); - - //transpose matrices - gsl_matrix *Y=gsl_matrix_alloc (d_size, n_size); - gsl_matrix *W=gsl_matrix_alloc (c_size, n_size); - gsl_matrix_transpose_memcpy (Y, UtY); - gsl_matrix_transpose_memcpy (W, UtW); - - //initial, EM, NR, and calculate B - MphInitial(em_iter, em_prec, nr_iter, nr_prec, eval, W, Y, l_min, l_max, n_region, V_g, V_e, B); - logl=MphEM ('R', em_iter, em_prec, eval, W, Y, U_hat, E_hat, OmegaU, OmegaE, UltVehiY, UltVehiBX, UltVehiU, UltVehiE, V_g, V_e, B); - logl=MphNR ('R', nr_iter, nr_prec, eval, W, Y, Hi_all, xHi_all, Hiy_all, V_g, V_e, Hessian, crt_a, crt_b, crt_c); - MphCalcBeta (eval, W, Y, V_g, V_e, UltVehiY, B, se_B); - - //free matrices - gsl_matrix_free(U_hat); - gsl_matrix_free(E_hat); - gsl_matrix_free(OmegaU); - gsl_matrix_free(OmegaE); - gsl_matrix_free(UltVehiY); - gsl_matrix_free(UltVehiBX); - gsl_matrix_free(UltVehiU); - gsl_matrix_free(UltVehiE); - - gsl_matrix_free(Hi_all); - gsl_matrix_free(Hiy_all); - gsl_matrix_free(xHi_all); - gsl_matrix_free(Hessian); - - gsl_matrix_free(Y); - gsl_matrix_free(W); - - return; -} - diff --git a/mvlmm.h b/mvlmm.h deleted file mode 100644 index 129879c..0000000 --- a/mvlmm.h +++ /dev/null @@ -1,94 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - -#ifndef __MVLMM_H__ -#define __MVLMM_H__ - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - - -#ifdef FORCE_FLOAT -#include "param_float.h" -#include "io_float.h" -#else -#include "param.h" -#include "io.h" -#endif - -using namespace std; - - - - - -class MVLMM { - -public: - // IO related parameters - int a_mode; //analysis mode, 1/2/3/4 for Frequentist tests - size_t d_pace; //display pace - - string file_bfile; - string file_geno; - string file_out; - string path_out; - - // MVLMM related parameters - double l_min; - double l_max; - size_t n_region; - double logl_remle_H0, logl_mle_H0; - vector<double> Vg_remle_null, Ve_remle_null, Vg_mle_null, Ve_mle_null; - vector<double> VVg_remle_null, VVe_remle_null, VVg_mle_null, VVe_mle_null; - vector<double> beta_remle_null, se_beta_remle_null, beta_mle_null, se_beta_mle_null; - double p_nr; - size_t em_iter, nr_iter; - double em_prec, nr_prec; - size_t crt; - - // Summary statistics - size_t ni_total, ni_test; //number of individuals - size_t ns_total, ns_test; //number of snps - size_t n_cvt; - size_t n_ph; - double time_UtX; //time spent on optimization iterations - double time_opt; //time spent on optimization iterations - - vector<int> indicator_idv; //indicator for individuals (phenotypes), 0 missing, 1 available for analysis - vector<int> indicator_snp; //sequence indicator for SNPs: 0 ignored because of (a) maf, (b) miss, (c) non-poly; 1 available for analysis - - vector<SNPINFO> snpInfo; //record SNP information - - // Not included in PARAM - vector<MPHSUMSTAT> sumStat; //Output SNPSummary Data - - // Main functions - void CopyFromParam (PARAM &cPar); - void CopyToParam (PARAM &cPar); - void AnalyzeBimbam (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_matrix *UtY); - void AnalyzePlink (const gsl_matrix *U, const gsl_vector *eval, const gsl_matrix *UtW, const gsl_matrix *UtY); - void WriteFiles (); - -}; - -void CalcMvLmmVgVeBeta (const gsl_vector *eval, const gsl_matrix *UtW, const gsl_matrix *UtY, const size_t em_iter, const size_t nr_iter, const double em_prec, const double nr_prec, const double l_min, const double l_max, const size_t n_region, gsl_matrix *V_g, gsl_matrix *V_e, gsl_matrix *B, gsl_matrix *se_B); - -#endif - - diff --git a/param.cpp b/param.cpp deleted file mode 100644 index 7a89ff8..0000000 --- a/param.cpp +++ /dev/null @@ -1,849 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#include <iostream> -#include <fstream> -#include <string> -#include <cstring> -#include <sys/stat.h> -#include <cmath> -#include <algorithm> - - -#ifdef FORCE_FLOAT -#include "param_float.h" -#include "io_float.h" -#else -#include "param.h" -#include "io.h" -#endif - -using namespace std; - - - - - -PARAM::PARAM(void): -mode_silence (false), a_mode (0), k_mode(1), d_pace (100000), -file_out("result"), path_out("./output/"), -miss_level(0.05), maf_level(0.01), hwe_level(0), r2_level(0.9999), -l_min(1e-5), l_max(1e5), n_region(10),p_nr(0.001),em_prec(0.0001),nr_prec(0.0001),em_iter(10000),nr_iter(100),crt(0), -pheno_mean(0), -h_min(-1), h_max(-1), h_scale(-1), -rho_min(0.0), rho_max(1.0), rho_scale(-1), -logp_min(0.0), logp_max(0.0), logp_scale(-1), -s_min(0), s_max(300), -w_step(100000), s_step(1000000), -r_pace(10), w_pace(1000), -n_accept(0), -n_mh(10), -geo_mean(2000.0), -randseed(-1), -error(false), - n_cvt(1), n_vc(1), -time_total(0.0), time_G(0.0), time_eigen(0.0), time_UtX(0.0), time_UtZ(0.0), time_opt(0.0), time_Omega(0.0) -{} - - -//read files -//obtain ns_total, ng_total, ns_test, ni_test -void PARAM::ReadFiles (void) -{ - string file_str; - if (!file_mk.empty()) { - if (CountFileLines (file_mk, n_vc)==false) {error=true;} - } - - if (!file_snps.empty()) { - if (ReadFile_snps (file_snps, setSnps)==false) {error=true;} - } else { - setSnps.clear(); - } - - //for prediction - if (!file_epm.empty()) { - if (ReadFile_est (file_epm, est_column, mapRS2est)==false) {error=true;} - - if (!file_bfile.empty()) { - file_str=file_bfile+".bim"; - if (ReadFile_bim (file_str, snpInfo)==false) {error=true;} - - file_str=file_bfile+".fam"; - if (ReadFile_fam (file_str, indicator_pheno, pheno, mapID2num, p_column)==false) {error=true;} - } - - if (!file_geno.empty()) { - if (ReadFile_pheno (file_pheno, indicator_pheno, pheno, p_column)==false) {error=true;} - - if (CountFileLines (file_geno, ns_total)==false) {error=true;} - } - - if (!file_ebv.empty() ) { - if (ReadFile_column (file_ebv, indicator_bv, vec_bv, 1)==false) {error=true;} - } - - if (!file_log.empty() ) { - if (ReadFile_log (file_log, pheno_mean)==false) {error=true;} - } - - //convert indicator_pheno to indicator_idv - int k=1; - for (size_t i=0; i<indicator_pheno.size(); i++) { - k=1; - for (size_t j=0; j<indicator_pheno[i].size(); j++) { - if (indicator_pheno[i][j]==0) {k=0;} - } - indicator_idv.push_back(k); - } - - ns_test=0; - - return; - } - - //read covariates before the genotype files - if (!file_cvt.empty() ) { - if (ReadFile_cvt (file_cvt, indicator_cvt, cvt, n_cvt)==false) {error=true;} - - if ((indicator_cvt).size()==0) { - n_cvt=1; - } - } else { - n_cvt=1; - } - - //read genotype and phenotype file for plink format - if (!file_bfile.empty()) { - file_str=file_bfile+".bim"; - if (ReadFile_bim (file_str, snpInfo)==false) {error=true;} - - file_str=file_bfile+".fam"; - if (ReadFile_fam (file_str, indicator_pheno, pheno, mapID2num, p_column)==false) {error=true;} - - //post-process covariates and phenotypes, obtain ni_test, save all useful covariates - ProcessCvtPhen(); - - //obtain covariate matrix - gsl_matrix *W=gsl_matrix_alloc (ni_test, n_cvt); - CopyCvt (W); - - file_str=file_bfile+".bed"; - if (ReadFile_bed (file_str, setSnps, W, indicator_idv, indicator_snp, snpInfo, maf_level, miss_level, hwe_level, r2_level, ns_test)==false) {error=true;} - - gsl_matrix_free(W); - - ns_total=indicator_snp.size(); - } - - //read genotype and phenotype file for bimbam format - if (!file_geno.empty()) { - //annotation file before genotype file - if (!file_anno.empty() ) { - if (ReadFile_anno (file_anno, mapRS2chr, mapRS2bp, mapRS2cM)==false) {error=true;} - } - - //phenotype file before genotype file - if (ReadFile_pheno (file_pheno, indicator_pheno, pheno, p_column)==false) {error=true;} - - //post-process covariates and phenotypes, obtain ni_test, save all useful covariates - ProcessCvtPhen(); - - //obtain covariate matrix - gsl_matrix *W=gsl_matrix_alloc (ni_test, n_cvt); - CopyCvt (W); - - if (ReadFile_geno (file_geno, setSnps, W, indicator_idv, indicator_snp, maf_level, miss_level, hwe_level, r2_level, mapRS2chr, mapRS2bp, mapRS2cM, snpInfo, ns_test)==false) {error=true;} - - gsl_matrix_free(W); - - ns_total=indicator_snp.size(); - } - - if (!file_gene.empty()) { - if (ReadFile_pheno (file_pheno, indicator_pheno, pheno, p_column)==false) {error=true;} - - //convert indicator_pheno to indicator_idv - int k=1; - for (size_t i=0; i<indicator_pheno.size(); i++) { - k=1; - for (size_t j=0; j<indicator_pheno[i].size(); j++) { - if (indicator_pheno[i][j]==0) {k=0;} - } - indicator_idv.push_back(k); - } - - if (ReadFile_gene (file_gene, vec_read, snpInfo, ng_total)==false) {error=true;} - } - - - //read is after gene file - if (!file_read.empty() ) { - if (ReadFile_column (file_read, indicator_read, vec_read, 1)==false) {error=true;} - - ni_test=0; - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - indicator_idv[i]*=indicator_read[i]; - ni_test+=indicator_idv[i]; - } - - if (ni_test==0) { - error=true; - cout<<"error! number of analyzed individuals equals 0. "<<endl; - return; - } - } - - //for ridge prediction, read phenotype only - if (file_geno.empty() && file_gene.empty() && !file_pheno.empty()) { - if (ReadFile_pheno (file_pheno, indicator_pheno, pheno, p_column)==false) {error=true;} - - //post-process covariates and phenotypes, obtain ni_test, save all useful covariates - ProcessCvtPhen(); - } - - return; -} - - - - - - -void PARAM::CheckParam (void) -{ - struct stat fileInfo; - string str; - - //check parameters - if (k_mode!=1 && k_mode!=2) {cout<<"error! unknown kinship/relatedness input mode: "<<k_mode<<endl; error=true;} - if (a_mode!=1 && a_mode!=2 && a_mode!=3 && a_mode!=4 && a_mode!=5 && a_mode!=11 && a_mode!=12 && a_mode!=13 && a_mode!=21 && a_mode!=22 && a_mode!=31 && a_mode!=41 && a_mode!=42 && a_mode!=43 && a_mode!=51 && a_mode!=52 && a_mode!=53 && a_mode!=54 && a_mode!=61) - {cout<<"error! unknown analysis mode: "<<a_mode<<". make sure -gk or -eigen or -lmm or -bslmm or -predict is sepcified correctly."<<endl; error=true;} - if (miss_level>1) {cout<<"error! missing level needs to be between 0 and 1. current value = "<<miss_level<<endl; error=true;} - if (maf_level>0.5) {cout<<"error! maf level needs to be between 0 and 0.5. current value = "<<maf_level<<endl; error=true;} - if (hwe_level>1) {cout<<"error! hwe level needs to be between 0 and 1. current value = "<<hwe_level<<endl; error=true;} - if (r2_level>1) {cout<<"error! r2 level needs to be between 0 and 1. current value = "<<r2_level<<endl; error=true;} - - if (l_max<l_min) {cout<<"error! maximum lambda value must be larger than the minimal value. current values = "<<l_max<<" and "<<l_min<<endl; error=true;} - if (h_max<h_min) {cout<<"error! maximum h value must be larger than the minimal value. current values = "<<h_max<<" and "<<h_min<<endl; error=true;} - if (s_max<s_min) {cout<<"error! maximum s value must be larger than the minimal value. current values = "<<s_max<<" and "<<s_min<<endl; error=true;} - if (rho_max<rho_min) {cout<<"error! maximum rho value must be larger than the minimal value. current values = "<<rho_max<<" and "<<rho_min<<endl; error=true;} - if (logp_max<logp_min) {cout<<"error! maximum logp value must be larger than the minimal value. current values = "<<logp_max/log(10)<<" and "<<logp_min/log(10)<<endl; error=true;} - - if (h_max>1) {cout<<"error! h values must be bewtween 0 and 1. current values = "<<h_max<<" and "<<h_min<<endl; error=true;} - if (rho_max>1) {cout<<"error! rho values must be between 0 and 1. current values = "<<rho_max<<" and "<<rho_min<<endl; error=true;} - if (logp_max>0) {cout<<"error! maximum logp value must be smaller than 0. current values = "<<logp_max/log(10)<<" and "<<logp_min/log(10)<<endl; error=true;} - if (l_max<l_min) {cout<<"error! maximum lambda value must be larger than the minimal value. current values = "<<l_max<<" and "<<l_min<<endl; error=true;} - - if (h_scale>1.0) {cout<<"error! hscale value must be between 0 and 1. current value = "<<h_scale<<endl; error=true;} - if (rho_scale>1.0) {cout<<"error! rscale value must be between 0 and 1. current value = "<<rho_scale<<endl; error=true;} - if (logp_scale>1.0) {cout<<"error! pscale value must be between 0 and 1. current value = "<<logp_scale<<endl; error=true;} - - if (rho_max==1 && rho_min==1 && a_mode==12) {cout<<"error! ridge regression does not support a rho parameter. current values = "<<rho_max<<" and "<<rho_min<<endl; error=true;} - - //check p_column, and (no need to) sort p_column into ascending order - if (p_column.size()==0) { - p_column.push_back(1); - } else { - for (size_t i=0; i<p_column.size(); i++) { - for (size_t j=0; j<i; j++) { - if (p_column[i]==p_column[j]) {cout<<"error! identical phenotype columns: "<<p_column[i]<<endl; error=true;} - } - } - } - - //sort (p_column.begin(), p_column.end() ); - n_ph=p_column.size(); - - - - //only lmm option (and one prediction option) can deal with multiple phenotypes - //and no gene expression files - if (n_ph>1 && a_mode!=1 && a_mode!=2 && a_mode!=3 && a_mode!=4 && a_mode!=43) { - cout<<"error! the current analysis mode "<<a_mode<<" can not deal with multiple phenotypes."<<endl; error=true; - } - if (n_ph>1 && !file_gene.empty() ) { - cout<<"error! multiple phenotype analysis option not allowed with gene expression files. "<<endl; error=true; - } - - if (p_nr>1) { - cout<<"error! pnr value must be between 0 and 1. current value = "<<p_nr<<endl; error=true; - } - - //check est_column - if (est_column.size()==0) { - if (file_ebv.empty()) { - est_column.push_back(2); - est_column.push_back(5); - est_column.push_back(6); - est_column.push_back(7); - } else { - est_column.push_back(2); - est_column.push_back(0); - est_column.push_back(6); - est_column.push_back(7); - } - } - - if (est_column.size()!=4) {cout<<"error! -en not followed by four numbers. current number = "<<est_column.size()<<endl; error=true;} - if (est_column[0]==0) {cout<<"error! -en rs column can not be zero. current number = "<<est_column.size()<<endl; error=true;} - - //check if files are compatible with each other, and if files exist - if (!file_bfile.empty()) { - str=file_bfile+".bim"; - if (stat(str.c_str(),&fileInfo)==-1) {cout<<"error! fail to open .bim file: "<<str<<endl; error=true;} - str=file_bfile+".bed"; - if (stat(str.c_str(),&fileInfo)==-1) {cout<<"error! fail to open .bed file: "<<str<<endl; error=true;} - str=file_bfile+".fam"; - if (stat(str.c_str(),&fileInfo)==-1) {cout<<"error! fail to open .fam file: "<<str<<endl; error=true;} - } - - if ((!file_geno.empty() || !file_gene.empty()) ) { - str=file_pheno; - if (stat(str.c_str(),&fileInfo)==-1) {cout<<"error! fail to open phenotype file: "<<str<<endl; error=true;} - } - - str=file_geno; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open mean genotype file: "<<str<<endl; error=true;} - - str=file_gene; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open gene expression file: "<<str<<endl; error=true;} - - size_t flag=0; - if (!file_bfile.empty()) {flag++;} - if (!file_geno.empty()) {flag++;} - if (!file_gene.empty()) {flag++;} - - if (flag!=1 && a_mode!=43 && a_mode!=5 && a_mode!=61) { - cout<<"error! either plink binary files, or bimbam mean genotype files, or gene expression files are required."<<endl; error=true; - } - - if (file_pheno.empty() && (a_mode==43 || a_mode==5 || a_mode==61) ) { - cout<<"error! phenotype file is required."<<endl; error=true; - } - - if (!file_epm.empty() && file_bfile.empty() && file_geno.empty() ) {cout<<"error! estimated parameter file also requires genotype file."<<endl; error=true;} - if (!file_ebv.empty() && file_kin.empty()) {cout<<"error! estimated breeding value file also requires relatedness file."<<endl; error=true;} - - if (!file_log.empty() && pheno_mean!=0) {cout<<"error! either log file or mu value can be provide."<<endl; error=true;} - - str=file_snps; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open snps file: "<<str<<endl; error=true;} - - str=file_log; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open log file: "<<str<<endl; error=true;} - - str=file_anno; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open annotation file: "<<str<<endl; error=true;} - - str=file_kin; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open relatedness matrix file: "<<str<<endl; error=true;} - - str=file_mk; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open relatedness matrix file: "<<str<<endl; error=true;} - - str=file_cvt; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open covariates file: "<<str<<endl; error=true;} - - str=file_epm; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open estimated parameter file: "<<str<<endl; error=true;} - - str=file_ebv; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open estimated breeding value file: "<<str<<endl; error=true;} - - str=file_read; - if (!str.empty() && stat(str.c_str(),&fileInfo)==-1 ) {cout<<"error! fail to open total read file: "<<str<<endl; error=true;} - - //check if files are compatible with analysis mode - if (k_mode==2 && !file_geno.empty() ) {cout<<"error! use \"-km 1\" when using bimbam mean genotype file. "<<endl; error=true;} - - if ((a_mode==1 || a_mode==2 || a_mode==3 || a_mode==4 || a_mode==5 || a_mode==31) && (file_kin.empty() && (file_ku.empty()||file_kd.empty())) ) {cout<<"error! missing relatedness file. "<<endl; error=true;} - - if (a_mode==61 && (file_kin.empty() && (file_ku.empty()||file_kd.empty()) && file_mk.empty() ) ) {cout<<"error! missing relatedness file. "<<endl; error=true;} - - if ((a_mode==43) && file_kin.empty()) {cout<<"error! missing relatedness file. -predict option requires -k option to provide a relatedness file."<<endl; error=true;} - - if ((a_mode==11 || a_mode==12 || a_mode==13) && !file_cvt.empty() ) {cout<<"error! -bslmm option does not support covariates files."<<endl; error=true;} - - if (a_mode==41 || a_mode==42) { - if (!file_cvt.empty() ) {cout<<"error! -predict option does not support covariates files."<<endl; error=true;} - if (file_epm.empty() ) {cout<<"error! -predict option requires estimated parameter files."<<endl; error=true;} - } - - return; -} - - - - - -void PARAM::CheckData (void) { - if ((file_cvt).empty() || (indicator_cvt).size()==0) { - n_cvt=1; - } - if ( (indicator_cvt).size()!=0 && (indicator_cvt).size()!=(indicator_idv).size()) { - error=true; - cout<<"error! number of rows in the covariates file do not match the number of individuals. "<<endl; - return; - } - - if ( (indicator_read).size()!=0 && (indicator_read).size()!=(indicator_idv).size()) { - error=true; - cout<<"error! number of rows in the total read file do not match the number of individuals. "<<endl; - return; - } - - //calculate ni_total and ni_test, and set indicator_idv to 0 whenever indicator_cvt=0 - //and calculate np_obs and np_miss - ni_total=(indicator_idv).size(); - - ni_test=0; - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - if (indicator_idv[i]==0) {continue;} - ni_test++; - } - - ni_cvt=0; - for (size_t i=0; i<indicator_cvt.size(); i++) { - if (indicator_cvt[i]==0) {continue;} - ni_cvt++; - } - - np_obs=0; np_miss=0; - for (size_t i=0; i<indicator_pheno.size(); i++) { - if (indicator_cvt.size()!=0) { - if (indicator_cvt[i]==0) {continue;} - } - - for (size_t j=0; j<indicator_pheno[i].size(); j++) { - if (indicator_pheno[i][j]==0) { - np_miss++; - } else { - np_obs++; - } - } - } - - /* - if ((indicator_cvt).size()!=0) { - ni_test=0; - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - indicator_idv[i]*=indicator_cvt[i]; - ni_test+=indicator_idv[i]; - } - } - - if ((indicator_read).size()!=0) { - ni_test=0; - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - indicator_idv[i]*=indicator_read[i]; - ni_test+=indicator_idv[i]; - } - } - */ - if (ni_test==0) { - error=true; - cout<<"error! number of analyzed individuals equals 0. "<<endl; - return; - } - - if (a_mode==43) { - if (ni_cvt==ni_test) { - error=true; - cout<<"error! no individual has missing phenotypes."<<endl; - return; - } - if ((np_obs+np_miss)!=(ni_cvt*n_ph)) { - error=true; - //cout<<ni_cvt<<"\t"<<ni_test<<"\t"<<ni_total<<"\t"<<np_obs<<"\t"<<np_miss<<"\t"<<indicator_cvt.size()<<endl; - cout<<"error! number of phenotypes do not match the summation of missing and observed phenotypes."<<endl; - return; - } - } - - //output some information - cout<<"## number of total individuals = "<<ni_total<<endl; - if (a_mode==43) { - cout<<"## number of analyzed individuals = "<<ni_cvt<<endl; - cout<<"## number of individuals with full phenotypes = "<<ni_test<<endl; - } else { - cout<<"## number of analyzed individuals = "<<ni_test<<endl; - } - cout<<"## number of covariates = "<<n_cvt<<endl; - cout<<"## number of phenotypes = "<<n_ph<<endl; - if (a_mode==43) { - cout<<"## number of observed data = "<<np_obs<<endl; - cout<<"## number of missing data = "<<np_miss<<endl; - } - if (!file_gene.empty()) { - cout<<"## number of total genes = "<<ng_total<<endl; - } else if (file_epm.empty() && a_mode!=43 && a_mode!=5) { - cout<<"## number of total SNPs = "<<ns_total<<endl; - cout<<"## number of analyzed SNPs = "<<ns_test<<endl; - } else {} - - //set d_pace to 1000 for gene expression - if (!file_gene.empty() && d_pace==100000) { - d_pace=1000; - } - - //for case-control studies, count #cases and #controls - int flag_cc=0; - if (a_mode==13) { - ni_case=0; - ni_control=0; - for (size_t i=0; i<indicator_idv.size(); i++) { - if (indicator_idv[i]==0) {continue;} - - if (pheno[i][0]==0) {ni_control++;} - else if (pheno[i][0]==1) {ni_case++;} - else {flag_cc=1;} - } - cout<<"## number of cases = "<<ni_case<<endl; - cout<<"## number of controls = "<<ni_control<<endl; - } - - if (flag_cc==1) {cout<<"Unexpected non-binary phenotypes for case/control analysis. Use default (BSLMM) analysis instead."<<endl; a_mode=11;} - - //set parameters for BSLMM - //and check for predict - if (a_mode==11 || a_mode==12 || a_mode==13) { - if (a_mode==11) {n_mh=1;} - if (logp_min==0) {logp_min=-1.0*log((double)ns_test);} - - if (h_scale==-1) {h_scale=min(1.0, 10.0/sqrt((double)ni_test) );} - if (rho_scale==-1) {rho_scale=min(1.0, 10.0/sqrt((double)ni_test) );} - if (logp_scale==-1) {logp_scale=min(1.0, 5.0/sqrt((double)ni_test) );} - - if (h_min==-1) {h_min=0.0;} - if (h_max==-1) {h_max=1.0;} - - if (s_max>ns_test) {s_max=ns_test; cout<<"s_max is re-set to the number of analyzed SNPs."<<endl;} - if (s_max<s_min) {cout<<"error! maximum s value must be larger than the minimal value. current values = "<<s_max<<" and "<<s_min<<endl; error=true;} - } else if (a_mode==41 || a_mode==42) { - if (indicator_bv.size()!=0) { - if (indicator_idv.size()!=indicator_bv.size()) { - cout<<"error! number of rows in the phenotype file does not match that in the estimated breeding value file: "<<indicator_idv.size()<<"\t"<<indicator_bv.size()<<endl; - error=true; - } else { - size_t flag_bv=0; - for (size_t i=0; i<(indicator_bv).size(); ++i) { - if (indicator_idv[i]!=indicator_bv[i]) {flag_bv++;} - } - if (flag_bv!=0) { - cout<<"error! individuals with missing value in the phenotype file does not match that in the estimated breeding value file: "<<flag_bv<<endl; - error=true; - } - } - } - } - - //file_mk needs to contain more than one line - if (n_vc==1 && !file_mk.empty()) {cout<<"error! -mk file should contain more than one line."<<endl; error=true;} - - return; -} - - -void PARAM::PrintSummary () -{ - if (n_ph==1) { - cout<<"pve estimate ="<<pve_null<<endl; - cout<<"se(pve) ="<<pve_se_null<<endl; - } else { - - } - return; -} - - - -void PARAM::ReadGenotypes (gsl_matrix *UtX, gsl_matrix *K, const bool calc_K) { - string file_str; - - if (!file_bfile.empty()) { - file_str=file_bfile+".bed"; - if (ReadFile_bed (file_str, indicator_idv, indicator_snp, UtX, K, calc_K)==false) {error=true;} - } - else { - if (ReadFile_geno (file_geno, indicator_idv, indicator_snp, UtX, K, calc_K)==false) {error=true;} - } - - return; -} - - - - -void PARAM::CalcKin (gsl_matrix *matrix_kin) { - string file_str; - - gsl_matrix_set_zero (matrix_kin); - - if (!file_bfile.empty() ) { - file_str=file_bfile+".bed"; - if (PlinkKin (file_str, indicator_snp, a_mode-20, d_pace, matrix_kin)==false) {error=true;} - } - else { - file_str=file_geno; - if (BimbamKin (file_str, indicator_snp, a_mode-20, d_pace, matrix_kin)==false) {error=true;} - } - - return; -} - - - - - -void PARAM::WriteMatrix (const gsl_matrix *matrix_U, const string suffix) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+="."; - file_str+=suffix; - file_str+=".txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - outfile.precision(10); - - for (size_t i=0; i<matrix_U->size1; ++i) { - for (size_t j=0; j<matrix_U->size2; ++j) { - outfile<<gsl_matrix_get (matrix_U, i, j)<<"\t"; - } - outfile<<endl; - } - - outfile.close(); - outfile.clear(); - return; -} - - -void PARAM::WriteVector (const gsl_vector *vector_D, const string suffix) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+="."; - file_str+=suffix; - file_str+=".txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - outfile.precision(10); - - for (size_t i=0; i<vector_D->size; ++i) { - outfile<<gsl_vector_get (vector_D, i)<<endl; - } - - outfile.close(); - outfile.clear(); - return; -} - - -void PARAM::CheckCvt () -{ - if (indicator_cvt.size()==0) {return;} - - size_t ci_test=0; - - gsl_matrix *W=gsl_matrix_alloc (ni_test, n_cvt); - - for (vector<int>::size_type i=0; i<indicator_idv.size(); ++i) { - if (indicator_idv[i]==0 || indicator_cvt[i]==0) {continue;} - for (size_t j=0; j<n_cvt; ++j) { - gsl_matrix_set (W, ci_test, j, (cvt)[i][j]); - } - ci_test++; - } - - size_t flag_ipt=0; - double v_min, v_max; - set<size_t> set_remove; - - //check if any columns is an intercept - for (size_t i=0; i<W->size2; i++) { - gsl_vector_view w_col=gsl_matrix_column (W, i); - gsl_vector_minmax (&w_col.vector, &v_min, &v_max); - if (v_min==v_max) {flag_ipt=1; set_remove.insert (i);} - } - - //add an intecept term if needed - if (n_cvt==set_remove.size()) { - indicator_cvt.clear(); - n_cvt=1; - } else if (flag_ipt==0) { - cout<<"no intecept term is found in the cvt file. a column of 1s is added."<<endl; - for (vector<int>::size_type i=0; i<indicator_idv.size(); ++i) { - if (indicator_idv[i]==0 || indicator_cvt[i]==0) {continue;} - cvt[i].push_back(1.0); - } - - n_cvt++; - } else {} - - gsl_matrix_free(W); - - return; -} - - -//post-process phentoypes, covariates -void PARAM::ProcessCvtPhen () -{ - //convert indicator_pheno to indicator_idv - int k=1; - indicator_idv.clear(); - for (size_t i=0; i<indicator_pheno.size(); i++) { - k=1; - for (size_t j=0; j<indicator_pheno[i].size(); j++) { - if (indicator_pheno[i][j]==0) {k=0;} - } - indicator_idv.push_back(k); - } - - //remove individuals with missing covariates - if ((indicator_cvt).size()!=0) { - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - indicator_idv[i]*=indicator_cvt[i]; - } - } - - //obtain ni_test - ni_test=0; - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - if (indicator_idv[i]==0) {continue;} - ni_test++; - } - - if (ni_test==0) { - error=true; - cout<<"error! number of analyzed individuals equals 0. "<<endl; - return; - } - - //check covariates to see if they are correlated with each other, and to see if the intercept term is included - //after getting ni_test - //add or remove covariates - if (indicator_cvt.size()!=0) { - CheckCvt(); - } else { - vector<double> cvt_row; - cvt_row.push_back(1); - - for (vector<int>::size_type i=0; i<(indicator_idv).size(); ++i) { - indicator_cvt.push_back(1); - - cvt.push_back(cvt_row); - } - } - - return; -} - - - - -void PARAM::CopyCvt (gsl_matrix *W) -{ - size_t ci_test=0; - - for (vector<int>::size_type i=0; i<indicator_idv.size(); ++i) { - if (indicator_idv[i]==0 || indicator_cvt[i]==0) {continue;} - for (size_t j=0; j<n_cvt; ++j) { - gsl_matrix_set (W, ci_test, j, (cvt)[i][j]); - } - ci_test++; - } - - return; -} - - -//if flag=0, then use indicator_idv to load W and Y -//else, use indicator_cvt to load them -void PARAM::CopyCvtPhen (gsl_matrix *W, gsl_vector *y, size_t flag) -{ - size_t ci_test=0; - - for (vector<int>::size_type i=0; i<indicator_idv.size(); ++i) { - if (flag==0) { - if (indicator_idv[i]==0) {continue;} - } else { - if (indicator_cvt[i]==0) {continue;} - } - - gsl_vector_set (y, ci_test, (pheno)[i][0]); - - for (size_t j=0; j<n_cvt; ++j) { - gsl_matrix_set (W, ci_test, j, (cvt)[i][j]); - } - ci_test++; - } - - return; -} - -//if flag=0, then use indicator_idv to load W and Y -//else, use indicator_cvt to load them -void PARAM::CopyCvtPhen (gsl_matrix *W, gsl_matrix *Y, size_t flag) -{ - size_t ci_test=0; - - for (vector<int>::size_type i=0; i<indicator_idv.size(); ++i) { - if (flag==0) { - if (indicator_idv[i]==0) {continue;} - } else { - if (indicator_cvt[i]==0) {continue;} - } - - for (size_t j=0; j<n_ph; ++j) { - gsl_matrix_set (Y, ci_test, j, (pheno)[i][j]); - } - for (size_t j=0; j<n_cvt; ++j) { - gsl_matrix_set (W, ci_test, j, (cvt)[i][j]); - } - ci_test++; - } - - return; -} - - - - - -void PARAM::CopyRead (gsl_vector *log_N) -{ - size_t ci_test=0; - - for (vector<int>::size_type i=0; i<indicator_idv.size(); ++i) { - if (indicator_idv[i]==0) {continue;} - gsl_vector_set (log_N, ci_test, log(vec_read[i]) ); - ci_test++; - } - - return; -} - - - diff --git a/param.h b/param.h deleted file mode 100644 index fa18181..0000000 --- a/param.h +++ /dev/null @@ -1,232 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __PARAM_H__ -#define __PARAM_H__ - -#include <vector> -#include <map> -#include <set> -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - -using namespace std; - - - -class SNPINFO { -public: - string chr; - string rs_number; - double cM; - long int base_position; - string a_minor; - string a_major; - size_t n_miss; - double missingness; - double maf; -}; - -//results for lmm -class SUMSTAT { -public: - double beta; //REML estimator for beta - double se; //SE for beta - double lambda_remle; //REML estimator for lambda - double lambda_mle; //MLE estimator for lambda - double p_wald; //p value from a Wald test - double p_lrt; //p value from a likelihood ratio test - double p_score; //p value from a score test -}; - -//results for mvlmm -class MPHSUMSTAT { -public: - vector<double> v_beta; //REML estimator for beta - double p_wald; //p value from a Wald test - double p_lrt; //p value from a likelihood ratio test - double p_score; //p value from a score test - vector<double> v_Vg; //estimator for Vg, right half - vector<double> v_Ve; //estimator for Ve, right half - vector<double> v_Vbeta; //estimator for Vbeta, right half -}; - - -//hyper-parameters for bslmm -class HYPBSLMM { -public: - double h; - double pve; - double rho; - double pge; - double logp; - - size_t n_gamma; -}; - - - - -class PARAM { -public: - // IO related parameters - bool mode_silence; - int a_mode; //analysis mode, 1/2/3/4 for Frequentist tests - int k_mode; //kinship read mode: 1: n by n matrix, 2: id/id/k_value; - vector<size_t> p_column; //which phenotype column needs analysis - size_t d_pace; //display pace - - string file_bfile; - string file_geno; - string file_pheno; - string file_anno; //optional - string file_cvt; //optional - string file_kin; - string file_ku, file_kd; - string file_mk; - string file_out; - string path_out; - - string file_epm; //estimated parameter file - string file_ebv; //estimated breeding value file - string file_log; //log file containing mean estimate - - string file_read; //file containing total number of reads - string file_gene; //gene expression file - - string file_snps; //file containing analyzed snps or genes - - - - // QC related parameters - double miss_level; - double maf_level; - double hwe_level; - double r2_level; - - // LMM related parameters - double l_min; - double l_max; - size_t n_region; - double l_mle_null, l_remle_null; - double logl_mle_H0, logl_remle_H0; - double pve_null, pve_se_null; - double vg_remle_null, ve_remle_null, vg_mle_null, ve_mle_null; - vector<double> Vg_remle_null, Ve_remle_null, Vg_mle_null, Ve_mle_null; - vector<double> VVg_remle_null, VVe_remle_null, VVg_mle_null, VVe_mle_null; - vector<double> beta_remle_null, se_beta_remle_null, beta_mle_null, se_beta_mle_null; - double p_nr; - double em_prec, nr_prec; - size_t em_iter, nr_iter; - size_t crt; - double pheno_mean; //phenotype mean from bslmm fitting or for prediction - - //for fitting multiple variance components - //the first three are of size n_vc, and the next two are of size n_vc+1 - vector<double> v_traceG; - vector<double> v_pve; - vector<double> v_se_pve; - - vector<double> v_sigma2; - vector<double> v_se_sigma2; - vector<double> v_beta; - vector<double> v_se_beta; - - // BSLMM MCMC related parameters - double h_min, h_max, h_scale; //priors for h - double rho_min, rho_max, rho_scale; //priors for rho - double logp_min, logp_max, logp_scale; //priors for log(pi) - size_t s_min, s_max; //minimum and maximum number of gammas - size_t w_step; //number of warm up/burn in iterations - size_t s_step; //number of sampling iterations - size_t r_pace; //record pace - size_t w_pace; //write pace - size_t n_accept; //number of acceptance - size_t n_mh; //number of MH steps within each iteration - double geo_mean; //mean of the geometric distribution - long int randseed; - double trace_G; - - HYPBSLMM cHyp_initial; - - // Summary statistics - bool error; - size_t ni_total, ni_test, ni_cvt; //number of individuals - size_t np_obs, np_miss; //number of observed and missing phenotypes - size_t ns_total, ns_test; //number of snps - size_t ng_total, ng_test; //number of genes - size_t ni_control, ni_case; //number of controls and number of cases - size_t n_cvt; //number of covariates - size_t n_ph; //number of phenotypes - size_t n_vc; //number of variance components (including the diagonal matrix) - double time_total; //record total time - double time_G; //time spent on reading files the second time and calculate K - double time_eigen; //time spent on eigen-decomposition - double time_UtX; //time spent on calculating UX and Uy - double time_UtZ; //time spent on calculating UtZ, for probit BSLMM - double time_opt; //time spent on optimization iterations/or mcmc - double time_Omega; //time spent on calculating Omega - double time_hyp; //time spent on sampling hyper-parameters, in PMM - double time_Proposal; //time spend on constructing the proposal distribution (i.e. the initial lmm or lm analysis) - - // Data - vector<vector<double> > pheno; //a vector record all phenotypes, NA replaced with -9 - vector<vector<double> > cvt; //a vector record all covariates, NA replaced with -9 - vector<vector<int> > indicator_pheno; //a matrix record when a phenotype is missing for an individual; 0 missing, 1 available - vector<int> indicator_idv; //indicator for individuals (phenotypes), 0 missing, 1 available for analysis - vector<int> indicator_snp; //sequence indicator for SNPs: 0 ignored because of (a) maf, (b) miss, (c) non-poly; 1 available for analysis - vector<int> indicator_cvt; //indicator for covariates, 0 missing, 1 available for analysis - - vector<int> indicator_bv; //indicator for estimated breeding value file, 0 missing, 1 available for analysis - vector<int> indicator_read; //indicator for read file, 0 missing, 1 available for analysis - vector<double> vec_read; //total number of reads - vector<double> vec_bv; //breeding values - vector<size_t> est_column; - - map<string, int> mapID2num; //map small ID number to number, from 0 to n-1 - map<string, string> mapRS2chr; //map rs# to chromosome location - map<string, long int> mapRS2bp; //map rs# to base position - map<string, double> mapRS2cM; //map rs# to cM - map<string, double> mapRS2est; //map rs# to parameters - - vector<SNPINFO> snpInfo; //record SNP information - set<string> setSnps; //a set of snps for analysis - - //constructor - PARAM(); - - //functions - void ReadFiles (); - void CheckParam (); - void CheckData (); - void PrintSummary (); - void ReadGenotypes (gsl_matrix *UtX, gsl_matrix *K, const bool calc_K); - void CheckCvt (); - void CopyCvt (gsl_matrix *W); - void ProcessCvtPhen(); - void CopyCvtPhen (gsl_matrix *W, gsl_vector *y, size_t flag); - void CopyCvtPhen (gsl_matrix *W, gsl_matrix *Y, size_t flag); - void CalcKin (gsl_matrix *matrix_kin); - void WriteMatrix (const gsl_matrix *matrix_U, const string suffix); - void WriteVector (const gsl_vector *vector_D, const string suffix); - void CopyRead (gsl_vector *log_N); -}; - - -#endif - diff --git a/prdt.cpp b/prdt.cpp deleted file mode 100644 index 2875119..0000000 --- a/prdt.cpp +++ /dev/null @@ -1,544 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - - - -#include <iostream> -#include <sstream> -#include <fstream> -#include <string> -#include <iomanip> -#include <bitset> -#include <vector> -#include <stdio.h> -#include <stdlib.h> -#include <cmath> -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" - - -#include "io.h" -#include "lapack.h" //for functions EigenDecomp -#include "gzstream.h" - -#ifdef FORCE_FLOAT -#include "io_float.h" -#include "prdt_float.h" -#include "mathfunc_float.h" -#else -#include "io.h" -#include "prdt.h" -#include "mathfunc.h" -#endif - -using namespace std; - - - - -void PRDT::CopyFromParam (PARAM &cPar) -{ - a_mode=cPar.a_mode; - d_pace=cPar.d_pace; - - file_bfile=cPar.file_bfile; - file_geno=cPar.file_geno; - file_out=cPar.file_out; - path_out=cPar.path_out; - - indicator_pheno=cPar.indicator_pheno; - indicator_cvt=cPar.indicator_cvt; - indicator_idv=cPar.indicator_idv; - - snpInfo=cPar.snpInfo; - mapRS2est=cPar.mapRS2est; - - time_eigen=0; - - n_ph=cPar.n_ph; - np_obs=cPar.np_obs; - np_miss=cPar.np_miss; - ns_total=cPar.ns_total; - ns_test=0; - - return; -} - -void PRDT::CopyToParam (PARAM &cPar) -{ - cPar.ns_test=ns_test; - cPar.time_eigen=time_eigen; - - return; -} - - - - -void PRDT::WriteFiles (gsl_vector *y_prdt) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+="."; - file_str+="prdt"; - file_str+=".txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - size_t ci_test=0; - for (size_t i=0; i<indicator_idv.size(); i++) { - if (indicator_idv[i]==1) { - outfile<<"NA"<<endl; - } else { - outfile<<gsl_vector_get (y_prdt, ci_test)<<endl; - ci_test++; - } - } - - outfile.close(); - outfile.clear(); - return; -} - - -void PRDT::WriteFiles (gsl_matrix *Y_full) -{ - string file_str; - file_str=path_out+"/"+file_out; - file_str+=".prdt.txt"; - - ofstream outfile (file_str.c_str(), ofstream::out); - if (!outfile) {cout<<"error writing file: "<<file_str.c_str()<<endl; return;} - - size_t ci_test=0; - for (size_t i=0; i<indicator_cvt.size(); i++) { - if (indicator_cvt[i]==0) { - outfile<<"NA"<<endl; - } else { - for (size_t j=0; j<Y_full->size2; j++) { - outfile<<gsl_matrix_get (Y_full, ci_test, j)<<"\t"; - } - outfile<<endl; - ci_test++; - } - } - - outfile.close(); - outfile.clear(); - return; -} - - - - -void PRDT::AddBV (gsl_matrix *G, const gsl_vector *u_hat, gsl_vector *y_prdt) -{ - size_t ni_test=u_hat->size, ni_total=G->size1; - - gsl_matrix *Goo=gsl_matrix_alloc (ni_test, ni_test); - gsl_matrix *Gfo=gsl_matrix_alloc (ni_total-ni_test, ni_test); - gsl_matrix *U=gsl_matrix_alloc (ni_test, ni_test); - gsl_vector *eval=gsl_vector_alloc (ni_test); - gsl_vector *Utu=gsl_vector_alloc (ni_test); - gsl_vector *w=gsl_vector_alloc (ni_total); - gsl_permutation *pmt=gsl_permutation_alloc (ni_test); - - //center matrix G based on indicator_idv - for (size_t i=0; i<ni_total; i++) { - gsl_vector_set(w, i, indicator_idv[i]); - } - CenterMatrix(G, w); - - //obtain Koo and Kfo - size_t o_i=0, o_j=0; - double d; - for (size_t i=0; i<indicator_idv.size(); i++) { - o_j=0; - for (size_t j=0; j<indicator_idv.size(); j++) { - d=gsl_matrix_get(G, i, j); - if (indicator_idv[i]==1 && indicator_idv[j]==1) { - gsl_matrix_set(Goo, o_i, o_j, d); - } - if (indicator_idv[i]==0 && indicator_idv[j]==1) { - gsl_matrix_set(Gfo, i-o_i, o_j, d); - } - if (indicator_idv[j]==1) {o_j++;} - } - if (indicator_idv[i]==1) {o_i++;} - } - - //matrix operations to get u_prdt - cout<<"Start Eigen-Decomposition..."<<endl; - clock_t time_start=clock(); - EigenDecomp (Goo, U, eval, 0); - for (size_t i=0; i<eval->size; i++) { - if (gsl_vector_get(eval,i)<1e-10) {gsl_vector_set(eval, i, 0);} - } - - time_eigen=(clock()-time_start)/(double(CLOCKS_PER_SEC)*60.0); - - gsl_blas_dgemv (CblasTrans, 1.0, U, u_hat, 0.0, Utu); - for (size_t i=0; i<eval->size; i++) { - d=gsl_vector_get(eval, i); - if (d!=0) {d=gsl_vector_get(Utu, i)/d; gsl_vector_set(Utu, i, d);} - } - gsl_blas_dgemv (CblasNoTrans, 1.0, U, Utu, 0.0, eval); - gsl_blas_dgemv (CblasNoTrans, 1.0, Gfo, eval, 1.0, y_prdt); - - //free matrices - gsl_matrix_free(Goo); - gsl_matrix_free(Gfo); - gsl_matrix_free(U); - gsl_vector_free(eval); - gsl_vector_free(Utu); - gsl_vector_free(w); - gsl_permutation_free(pmt); - - return; -} - - - -void PRDT::AnalyzeBimbam (gsl_vector *y_prdt) -{ - igzstream infile (file_geno.c_str(), igzstream::in); -// ifstream infile (file_geno.c_str(), ifstream::in); - if (!infile) {cout<<"error reading genotype file:"<<file_geno<<endl; return;} - - string line; - char *ch_ptr; - string rs; - - size_t n_miss, n_train_nomiss, c_phen; - double geno, x_mean, x_train_mean, effect_size; - - gsl_vector *x=gsl_vector_alloc (y_prdt->size); - gsl_vector *x_miss=gsl_vector_alloc (y_prdt->size); - - ns_test=0; - - //start reading genotypes and analyze - for (size_t t=0; t<ns_total; ++t) { - !safeGetline(infile, line).eof(); - if (t%d_pace==0 || t==(ns_total-1)) {ProgressBar ("Reading SNPs ", t, ns_total-1);} - - ch_ptr=strtok ((char *)line.c_str(), " , \t"); - rs=ch_ptr; - ch_ptr=strtok (NULL, " , \t"); - ch_ptr=strtok (NULL, " , \t"); - - if (mapRS2est.count(rs)==0) {continue;} else {effect_size=mapRS2est[rs];} - - x_mean=0.0; c_phen=0; n_miss=0; x_train_mean=0; n_train_nomiss=0; - gsl_vector_set_zero(x_miss); - - for (size_t i=0; i<indicator_idv.size(); ++i) { - ch_ptr=strtok (NULL, " , \t"); - if (indicator_idv[i]==1) { - if (strcmp(ch_ptr, "NA")!=0) { - geno=atof(ch_ptr); - x_train_mean+=geno; - n_train_nomiss++; - } - } else { - if (strcmp(ch_ptr, "NA")==0) { - gsl_vector_set(x_miss, c_phen, 0.0); n_miss++; - } else { - geno=atof(ch_ptr); - - gsl_vector_set(x, c_phen, geno); - gsl_vector_set(x_miss, c_phen, 1.0); - x_mean+=geno; - } - c_phen++; - } - } - - if (x->size==n_miss) {cout<<"snp "<<rs<<" has missing genotype for all individuals and will be ignored."<<endl; continue;} - - x_mean/=(double)(x->size-n_miss); - x_train_mean/=(double)(n_train_nomiss); - - - for (size_t i=0; i<x->size; ++i) { - geno=gsl_vector_get(x, i); - if (gsl_vector_get (x_miss, i)==0) { - gsl_vector_set(x, i, x_mean-x_train_mean); - } else { - gsl_vector_set(x, i, geno-x_train_mean); - } - } - - gsl_vector_scale (x, effect_size); - gsl_vector_add (y_prdt, x); - - ns_test++; - } - cout<<endl; - - gsl_vector_free (x); - gsl_vector_free (x_miss); - - infile.close(); - infile.clear(); - - return; -} - - - - - - - -void PRDT::AnalyzePlink (gsl_vector *y_prdt) -{ - string file_bed=file_bfile+".bed"; - ifstream infile (file_bed.c_str(), ios::binary); - if (!infile) {cout<<"error reading bed file:"<<file_bed<<endl; return;} - - char ch[1]; - bitset<8> b; - string rs; - - size_t n_bit, n_miss, ci_total, ci_test, n_train_nomiss; - double geno, x_mean, x_train_mean, effect_size; - - gsl_vector *x=gsl_vector_alloc (y_prdt->size); - - //calculate n_bit and c, the number of bit for each snp - if (indicator_idv.size()%4==0) {n_bit=indicator_idv.size()/4;} - else {n_bit=indicator_idv.size()/4+1; } - - //print the first three majic numbers - for (size_t i=0; i<3; ++i) { - infile.read(ch,1); - b=ch[0]; - } - - ns_test=0; - - for (vector<SNPINFO>::size_type t=0; t<snpInfo.size(); ++t) { - if (t%d_pace==0 || t==snpInfo.size()-1) {ProgressBar ("Reading SNPs ", t, snpInfo.size()-1);} - //if (indicator_snp[t]==0) {continue;} - - rs=snpInfo[t].rs_number; - - if (mapRS2est.count(rs)==0) {continue;} else {effect_size=mapRS2est[rs];} - - infile.seekg(t*n_bit+3); //n_bit, and 3 is the number of magic numbers - - //read genotypes - x_mean=0.0; n_miss=0; ci_total=0; ci_test=0; x_train_mean=0; n_train_nomiss=0; - for (size_t i=0; i<n_bit; ++i) { - infile.read(ch,1); - b=ch[0]; - for (size_t j=0; j<4; ++j) { //minor allele homozygous: 2.0; major: 0.0; - if ((i==(n_bit-1)) && ci_total==indicator_idv.size() ) {break;} - if (indicator_idv[ci_total]==1) { - if (b[2*j]==0) { - if (b[2*j+1]==0) {x_train_mean+=2.0; n_train_nomiss++;} - else {x_train_mean+=1.0; n_train_nomiss++;} - } - else { - if (b[2*j+1]==1) {n_train_nomiss++;} - else {} - } - } else { - if (b[2*j]==0) { - if (b[2*j+1]==0) {gsl_vector_set(x, ci_test, 2); x_mean+=2.0; } - else {gsl_vector_set(x, ci_test, 1); x_mean+=1.0; } - } - else { - if (b[2*j+1]==1) {gsl_vector_set(x, ci_test, 0); } - else {gsl_vector_set(x, ci_test, -9); n_miss++; } - } - ci_test++; - } - ci_total++; - - } - } - - if (x->size==n_miss) {cout<<"snp "<<rs<<" has missing genotype for all individuals and will be ignored."<<endl; continue;} - - x_mean/=(double)(x->size-n_miss); - x_train_mean/=(double)(n_train_nomiss); - - for (size_t i=0; i<x->size; ++i) { - geno=gsl_vector_get(x, i); - if (geno==-9) { - gsl_vector_set(x, i, x_mean-x_train_mean); - } else { - gsl_vector_set(x, i, geno-x_train_mean); - } - } - - gsl_vector_scale (x, effect_size); - gsl_vector_add (y_prdt, x); - - ns_test++; - } - cout<<endl; - - gsl_vector_free (x); - - infile.close(); - infile.clear(); - - return; -} - - - - -//predict missing phenotypes using ridge regression -//Y_hat contains fixed effects -void PRDT::MvnormPrdt (const gsl_matrix *Y_hat, const gsl_matrix *H, gsl_matrix *Y_full) -{ - gsl_vector *y_obs=gsl_vector_alloc (np_obs); - gsl_vector *y_miss=gsl_vector_alloc (np_miss); - gsl_matrix *H_oo=gsl_matrix_alloc (np_obs, np_obs); - gsl_matrix *H_mo=gsl_matrix_alloc (np_miss, np_obs); - gsl_vector *Hiy=gsl_vector_alloc (np_obs); - - size_t c_obs1=0, c_obs2=0, c_miss1=0, c_miss2=0; - - //obtain H_oo, H_mo - c_obs1=0; c_miss1=0; - for (vector<int>::size_type i1=0; i1<indicator_pheno.size(); ++i1) { - if (indicator_cvt[i1]==0) {continue;} - for (vector<int>::size_type j1=0; j1<n_ph; ++j1) { - - c_obs2=0; c_miss2=0; - for (vector<int>::size_type i2=0; i2<indicator_pheno.size(); ++i2) { - if (indicator_cvt[i2]==0) {continue;} - for (vector<int>::size_type j2=0; j2<n_ph; j2++) { - - if (indicator_pheno[i2][j2]==1) { - if (indicator_pheno[i1][j1]==1) { - gsl_matrix_set (H_oo, c_obs1, c_obs2, gsl_matrix_get (H, c_obs1+c_miss1, c_obs2+c_miss2) ); - } else { - gsl_matrix_set (H_mo, c_miss1, c_obs2, gsl_matrix_get (H, c_obs1+c_miss1, c_obs2+c_miss2) ); - } - c_obs2++; - } else { - c_miss2++; - } - } - } - - if (indicator_pheno[i1][j1]==1) { - c_obs1++; - } else { - c_miss1++; - } - } - - } - - //do LU decomposition of H_oo - int sig; - gsl_permutation * pmt=gsl_permutation_alloc (np_obs); - LUDecomp (H_oo, pmt, &sig); - -// if (mode_temp==0) { - //obtain y_obs=y_full-y_hat - //add the fixed effects part to y_miss: y_miss=y_hat - c_obs1=0; c_miss1=0; - for (vector<int>::size_type i=0; i<indicator_pheno.size(); ++i) { - if (indicator_cvt[i]==0) {continue;} - - for (vector<int>::size_type j=0; j<n_ph; ++j) { - if (indicator_pheno[i][j]==1) { - gsl_vector_set (y_obs, c_obs1, gsl_matrix_get (Y_full, i, j)-gsl_matrix_get (Y_hat, i, j) ); - c_obs1++; - } else { - gsl_vector_set (y_miss, c_miss1, gsl_matrix_get (Y_hat, i, j) ); - c_miss1++; - } - } - } - - LUSolve (H_oo, pmt, y_obs, Hiy); - - gsl_blas_dgemv (CblasNoTrans, 1.0, H_mo, Hiy, 1.0, y_miss); - - //put back predicted y_miss to Y_full - c_miss1=0; - for (vector<int>::size_type i=0; i<indicator_pheno.size(); ++i) { - if (indicator_cvt[i]==0) {continue;} - - for (vector<int>::size_type j=0; j<n_ph; ++j) { - if (indicator_pheno[i][j]==0) { - gsl_matrix_set (Y_full, i, j, gsl_vector_get (y_miss, c_miss1) ); - c_miss1++; - } - } - } -/* - } else { - for (size_t k=0; k<mode_temp; k++) { - c_obs1=0; c_miss1=0; - for (vector<int>::size_type i=0; i<indicator_pheno.size(); ++i) { - if (indicator_cvt[i]==0) {continue;} - - for (vector<int>::size_type j=0; j<2; ++j) { - if (indicator_pheno[i][j]==1) { - gsl_vector_set (y_obs, c_obs1, gsl_matrix_get (Y_full, i, j+k*2)-gsl_matrix_get (Y_hat, i, j) ); - c_obs1++; - } else { - gsl_vector_set (y_miss, c_miss1, gsl_matrix_get (Y_hat, i, j) ); - c_miss1++; - } - } - } - - LUSolve (H_oo, pmt, y_obs, Hiy); - - gsl_blas_dgemv (CblasNoTrans, 1.0, H_mo, Hiy, 1.0, y_miss); - - //put back predicted y_miss to Y_full - c_miss1=0; - for (vector<int>::size_type i=0; i<indicator_pheno.size(); ++i) { - if (indicator_cvt[i]==0) {continue;} - - for (vector<int>::size_type j=0; j<2; ++j) { - if (indicator_pheno[i][j]==0) { - gsl_matrix_set (Y_full, i, j+k*2, gsl_vector_get (y_miss, c_miss1) ); - c_miss1++; - } - } - } - } - } -*/ - //free matrices - gsl_vector_free(y_obs); - gsl_vector_free(y_miss); - gsl_matrix_free(H_oo); - gsl_matrix_free(H_mo); - gsl_vector_free(Hiy); - - return; -} - - diff --git a/prdt.h b/prdt.h deleted file mode 100644 index 8af2cee..0000000 --- a/prdt.h +++ /dev/null @@ -1,81 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __PRDT_H__ -#define __PRDT_H__ - - -#include <vector> -#include <map> -#include <string.h> -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - -#ifdef FORCE_FLOAT -#include "param_float.h" -#else -#include "param.h" -#endif - -using namespace std; - -class PRDT { - -public: - // IO related parameters - size_t a_mode; - size_t d_pace; - - string file_bfile; - string file_geno; - string file_out; - string path_out; - - vector<vector<int> > indicator_pheno; - vector<int> indicator_cvt; - vector<int> indicator_idv; - vector<SNPINFO> snpInfo; - map<string, double> mapRS2est; - - size_t n_ph; - size_t np_obs, np_miss; - size_t ns_total; - size_t ns_test; - - double time_eigen; - - // Main functions - void CopyFromParam (PARAM &cPar); - void CopyToParam (PARAM &cPar); - void WriteFiles (gsl_vector *y_prdt); - void WriteFiles (gsl_matrix *Y_full); - void AddBV (gsl_matrix *G, const gsl_vector *u_hat, gsl_vector *y_prdt); - void AnalyzeBimbam (gsl_vector *y_prdt); - void AnalyzePlink (gsl_vector *y_prdt); - void MvnormPrdt (const gsl_matrix *Y_hat, const gsl_matrix *H, gsl_matrix *Y_full); -}; - - -#endif - - - - - - - diff --git a/vc.cpp b/vc.cpp deleted file mode 100644 index 77cf746..0000000 --- a/vc.cpp +++ /dev/null @@ -1,443 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - - - -#include <iostream> -#include <fstream> -#include <sstream> - -#include <iomanip> -#include <cmath> -#include <iostream> -#include <stdio.h> -#include <stdlib.h> -#include <bitset> -#include <cstring> - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" -#include "gsl/gsl_linalg.h" -#include "gsl/gsl_blas.h" - -#include "gsl/gsl_cdf.h" -#include "gsl/gsl_multiroots.h" -#include "gsl/gsl_min.h" - -#include "io.h" -#include "lapack.h" -#include "gzstream.h" - -#ifdef FORCE_FLOAT -#include "lmm_float.h" -#include "vc_float.h" -#else -#include "lmm.h" -#include "vc.h" -#endif - - - -using namespace std; - - -//in this file, X, Y are already transformed (i.e. UtX and UtY) - - -void VC::CopyFromParam (PARAM &cPar) -{ - file_out=cPar.file_out; - - // v_sigma2=cPar.v_sigma2; - - time_UtX=0.0; - time_opt=0.0; - - v_traceG=cPar.v_traceG; - - return; -} - - -void VC::CopyToParam (PARAM &cPar) -{ - cPar.time_UtX=time_UtX; - cPar.time_opt=time_opt; - - cPar.v_sigma2=v_sigma2; - cPar.v_se_sigma2=v_se_sigma2; - cPar.v_pve=v_pve; - cPar.v_se_pve=v_se_pve; - cPar.v_traceG=v_traceG; - - cPar.v_beta=v_beta; - cPar.v_se_beta=v_se_beta; - - return; -} - - - -void UpdateParam (const gsl_vector *log_sigma2, VC_PARAM *p) -{ - size_t n1=(p->K)->size1, n_vc=log_sigma2->size-1, n_cvt=(p->W)->size2; - - gsl_matrix *K_temp=gsl_matrix_alloc(n1, n1); - gsl_matrix *HiW=gsl_matrix_alloc(n1, n_cvt); - gsl_matrix *WtHiW=gsl_matrix_alloc(n_cvt, n_cvt); - gsl_matrix *WtHiWi=gsl_matrix_alloc(n_cvt, n_cvt); - gsl_matrix *WtHiWiWtHi=gsl_matrix_alloc(n_cvt, n1); - - double sigma2; - //calculate H=\sum_i^{k+1} \sigma_i^2 K_i - gsl_matrix_set_zero (p->P); - for (size_t i=0; i<n_vc+1; i++) { - if (i==n_vc) { - gsl_matrix_set_identity (K_temp); - } else { - gsl_matrix_const_view K_sub=gsl_matrix_const_submatrix (p->K, 0, n1*i, n1, n1); - gsl_matrix_memcpy (K_temp, &K_sub.matrix); - } - - sigma2=exp(gsl_vector_get (log_sigma2, i) ); - gsl_matrix_scale(K_temp, sigma2); - gsl_matrix_add (p->P, K_temp); - } - - //calculate H^{-1} - int sig; - gsl_permutation * pmt1=gsl_permutation_alloc (n1); - LUDecomp (p->P, pmt1, &sig); - LUInvert (p->P, pmt1, K_temp); - gsl_permutation_free(pmt1); - - gsl_matrix_memcpy (p->P, K_temp); - - //calculate P=H^{-1}-H^{-1}W(W^TH^{-1}W)^{-1}W^TH^{-1} - gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, 1.0, p->P, p->W, 0.0, HiW); - gsl_blas_dgemm (CblasTrans, CblasNoTrans, 1.0, p->W, HiW, 0.0, WtHiW); - - gsl_permutation * pmt2=gsl_permutation_alloc (n_cvt); - LUDecomp (WtHiW, pmt2, &sig); - LUInvert (WtHiW, pmt2, WtHiWi); - gsl_permutation_free(pmt2); - - gsl_blas_dgemm (CblasNoTrans, CblasTrans, 1.0, WtHiWi, HiW, 0.0, WtHiWiWtHi); - gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, -1.0, HiW, WtHiWiWtHi, 1.0, p->P); - - //calculate Py, KPy, PKPy - gsl_blas_dgemv(CblasNoTrans, 1.0, p->P, p->y, 0.0, p->Py); - - for (size_t i=0; i<n_vc+1; i++) { - gsl_vector_view KPy=gsl_matrix_column (p->KPy_mat, i); - gsl_vector_view PKPy=gsl_matrix_column (p->PKPy_mat, i); - - if (i==n_vc) { - gsl_vector_memcpy (&KPy.vector, p->Py); - } else { - gsl_matrix_const_view K_sub=gsl_matrix_const_submatrix (p->K, 0, n1*i, n1, n1); - gsl_blas_dgemv(CblasNoTrans, 1.0, &K_sub.matrix, p->Py, 0.0, &KPy.vector); - } - - gsl_blas_dgemv(CblasNoTrans, 1.0, p->P, &KPy.vector, 0.0, &PKPy.vector); - } - - gsl_matrix_free (K_temp); - gsl_matrix_free (HiW); - gsl_matrix_free (WtHiW); - gsl_matrix_free (WtHiWi); - gsl_matrix_free (WtHiWiWtHi); - - return; -} - - -//below are functions for AI algorithm -int LogRL_dev1 (const gsl_vector *log_sigma2, void *params, gsl_vector *dev1) -{ - VC_PARAM *p=(VC_PARAM *) params; - - size_t n1=(p->K)->size1, n_vc=log_sigma2->size-1; - - double tr, d; - - //update parameters - UpdateParam (log_sigma2, p); - - //calculate dev1=-0.5*trace(PK_i)+0.5*yPKPy - for (size_t i=0; i<n_vc+1; i++) { - if (i==n_vc) { - tr=0; - for (size_t l=0; l<n1; l++) { - tr+=gsl_matrix_get (p->P, l, l); - } - } else { - tr=0; - for (size_t l=0; l<n1; l++) { - gsl_vector_view P_row=gsl_matrix_row (p->P, l); - gsl_vector_const_view K_col=gsl_matrix_const_column (p->K, n1*i+l); - gsl_blas_ddot(&P_row.vector, &K_col.vector, &d); - tr+=d; - } - } - - gsl_vector_view KPy_i=gsl_matrix_column (p->KPy_mat, i); - gsl_blas_ddot(p->Py, &KPy_i.vector, &d); - - d=(-0.5*tr+0.5*d)*exp(gsl_vector_get(log_sigma2, i)); - - gsl_vector_set(dev1, i, d); - } - - return GSL_SUCCESS; -} - - - -int LogRL_dev2 (const gsl_vector *log_sigma2, void *params, gsl_matrix *dev2) -{ - VC_PARAM *p=(VC_PARAM *) params; - - size_t n_vc=log_sigma2->size-1; - - double d, sigma2_i, sigma2_j; - - //update parameters - UpdateParam (log_sigma2, p); - - //calculate dev2=0.5(yPKPKPy) - for (size_t i=0; i<n_vc+1; i++) { - gsl_vector_view KPy_i=gsl_matrix_column (p->KPy_mat, i); - sigma2_i=exp(gsl_vector_get(log_sigma2, i)); - - for (size_t j=i; j<n_vc+1; j++) { - gsl_vector_view PKPy_j=gsl_matrix_column (p->PKPy_mat, j); - - gsl_blas_ddot(&KPy_i.vector, &PKPy_j.vector, &d); - sigma2_j=exp(gsl_vector_get(log_sigma2, j)); - - d*=-0.5*sigma2_i*sigma2_j; - - gsl_matrix_set(dev2, i, j, d); - if (j!=i) {gsl_matrix_set(dev2, j, i, d);} - } - } - - gsl_matrix_memcpy (p->Hessian, dev2); - - return GSL_SUCCESS; -} - - - -int LogRL_dev12 (const gsl_vector *log_sigma2, void *params, gsl_vector *dev1, gsl_matrix *dev2) -{ - VC_PARAM *p=(VC_PARAM *) params; - - size_t n1=(p->K)->size1, n_vc=log_sigma2->size-1; - - double tr, d, sigma2_i, sigma2_j; - - //update parameters - UpdateParam (log_sigma2, p); - - //calculate dev1=-0.5*trace(PK_i)+0.5*yPKPy - //calculate dev2=0.5(yPKPKPy) - for (size_t i=0; i<n_vc+1; i++) { - if (i==n_vc) { - tr=0; - for (size_t l=0; l<n1; l++) { - tr+=gsl_matrix_get (p->P, l, l); - } - } else { - tr=0; - for (size_t l=0; l<n1; l++) { - gsl_vector_view P_row=gsl_matrix_row (p->P, l); - gsl_vector_const_view K_col=gsl_matrix_const_column (p->K, n1*i+l); - gsl_blas_ddot(&P_row.vector, &K_col.vector, &d); - tr+=d; - } - } - - gsl_vector_view KPy_i=gsl_matrix_column (p->KPy_mat, i); - gsl_blas_ddot(p->Py, &KPy_i.vector, &d); - - sigma2_i=exp(gsl_vector_get(log_sigma2, i)); - d=(-0.5*tr+0.5*d)*sigma2_i; - - gsl_vector_set(dev1, i, d); - - for (size_t j=i; j<n_vc+1; j++) { - gsl_vector_view PKPy_j=gsl_matrix_column (p->PKPy_mat, j); - gsl_blas_ddot(&KPy_i.vector, &PKPy_j.vector, &d); - - sigma2_j=exp(gsl_vector_get(log_sigma2, j)); - d*=-0.5*sigma2_i*sigma2_j; - - gsl_matrix_set(dev2, i, j, d); - if (j!=i) {gsl_matrix_set(dev2, j, i, d);} - } - - } - - gsl_matrix_memcpy (p->Hessian, dev2); - - return GSL_SUCCESS; -} - - - - -void VC::CalcVCreml (const gsl_matrix *K, const gsl_matrix *W, const gsl_vector *y) -{ - size_t n1=K->size1, n2=K->size2; - size_t n_vc=n2/n1; - gsl_vector *log_sigma2=gsl_vector_alloc (n_vc+1); - double d, s; - - //set up params - gsl_matrix *P=gsl_matrix_alloc (n1, n1); - gsl_vector *Py=gsl_vector_alloc (n1); - gsl_matrix *KPy_mat=gsl_matrix_alloc (n1, n_vc+1); - gsl_matrix *PKPy_mat=gsl_matrix_alloc (n1, n_vc+1); - gsl_vector *dev1=gsl_vector_alloc (n_vc+1); - gsl_matrix *dev2=gsl_matrix_alloc (n_vc+1, n_vc+1); - gsl_matrix *Hessian=gsl_matrix_alloc (n_vc+1, n_vc+1); - VC_PARAM params={K, W, y, P, Py, KPy_mat, PKPy_mat, Hessian}; - - //initialize sigma2/log_sigma2 - gsl_blas_ddot (y, y, &s); - s/=(double)n1; - for (size_t i=0; i<n_vc+1; i++) { - if (i==n_vc) { - d=s/((double)n_vc+1.0); - } else { - d=s/( ((double)n_vc+1.0)*v_traceG[i]); - } - - gsl_vector_set (log_sigma2, i, d); - } - // gsl_vector_set (log_sigma2, 0, 0.38); - // gsl_vector_set (log_sigma2, 1, -1.08); - - cout<<"iteration "<<0<<endl; - cout<<"sigma2 = "; - for (size_t i=0; i<n_vc+1; i++) { - cout<<exp(gsl_vector_get(log_sigma2, i))<<" "; - } - cout<<endl; - - //set up fdf - gsl_multiroot_function_fdf FDF; - FDF.n=n_vc+1; - FDF.params=¶ms; - FDF.f=&LogRL_dev1; - FDF.df=&LogRL_dev2; - FDF.fdf=&LogRL_dev12; - - //set up solver - int status; - int iter=0, max_iter=100; - - const gsl_multiroot_fdfsolver_type *T_fdf; - gsl_multiroot_fdfsolver *s_fdf; - T_fdf=gsl_multiroot_fdfsolver_hybridsj; - s_fdf=gsl_multiroot_fdfsolver_alloc (T_fdf, n_vc+1); - - gsl_multiroot_fdfsolver_set (s_fdf, &FDF, log_sigma2); - - do { - iter++; - status=gsl_multiroot_fdfsolver_iterate (s_fdf); - - if (status) break; - - cout<<"iteration "<<iter<<endl; - cout<<"sigma2 = "; - for (size_t i=0; i<n_vc+1; i++) { - cout<<exp(gsl_vector_get(s_fdf->x, i))<<" "; - } - cout<<endl; - cout<<"derivatives = "; - for (size_t i=0; i<n_vc+1; i++) { - cout<<gsl_vector_get(s_fdf->f, i)<<" "; - } - cout<<endl; - - status=gsl_multiroot_test_residual (s_fdf->f, 1e-3); - } - while (status==GSL_CONTINUE && iter<max_iter); - - //obtain Hessian inverse - int sig=LogRL_dev12 (s_fdf->f, ¶ms, dev1, dev2); - - gsl_permutation * pmt=gsl_permutation_alloc (n_vc+1); - LUDecomp (dev2, pmt, &sig); - LUInvert (dev2, pmt, Hessian); - gsl_permutation_free(pmt); - - //save data - v_sigma2.clear(); - for (size_t i=0; i<n_vc+1; i++) { - d=exp(gsl_vector_get(s_fdf->x, i)); - v_sigma2.push_back(d); - } - - v_se_sigma2.clear(); - for (size_t i=0; i<n_vc+1; i++) { - d=-1.0*v_sigma2[i]*v_sigma2[i]*gsl_matrix_get(Hessian, i, i); - v_se_sigma2.push_back(sqrt(d)); - } - - s=0; - for (size_t i=0; i<n_vc; i++) { - s+=v_traceG[i]*v_sigma2[i]; - } - s+=v_sigma2[n_vc]; - - v_pve.clear(); - for (size_t i=0; i<n_vc; i++) { - d=v_traceG[i]*v_sigma2[i]/s; - v_pve.push_back(d); - } - - v_se_pve.clear(); - for (size_t i=0; i<n_vc; i++) { - d=v_traceG[i]*(s-v_sigma2[i]*v_traceG[i])/(s*s)*v_se_sigma2[i]*v_se_sigma2[i]; - v_se_pve.push_back(sqrt(d) ); - } - - gsl_multiroot_fdfsolver_free(s_fdf); - - gsl_vector_free(log_sigma2); - gsl_matrix_free(P); - gsl_vector_free(Py); - gsl_matrix_free(KPy_mat); - gsl_matrix_free(PKPy_mat); - gsl_vector_free(dev1); - gsl_matrix_free(dev2); - gsl_matrix_free(Hessian); - - return; -} - - - - - - diff --git a/vc.h b/vc.h deleted file mode 100644 index f34d72e..0000000 --- a/vc.h +++ /dev/null @@ -1,82 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011 Xiang Zhou - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see <http://www.gnu.org/licenses/>. -*/ - -#ifndef __VC_H__ -#define __VC_H__ - -#include "gsl/gsl_vector.h" -#include "gsl/gsl_matrix.h" - - -#ifdef FORCE_FLOAT -#include "param_float.h" -#include "io_float.h" -#else -#include "param.h" -#include "io.h" -#endif - -using namespace std; - - - -class VC_PARAM -{ - -public: - const gsl_matrix *K; - const gsl_matrix *W; - const gsl_vector *y; - gsl_matrix *P; - gsl_vector *Py; - gsl_matrix *KPy_mat; - gsl_matrix *PKPy_mat; - gsl_matrix *Hessian; -}; - - - - -class VC { - -public: - // IO related parameters - string file_out; - string path_out; - - vector<double> v_sigma2; - vector<double> v_se_sigma2; - vector<double> v_pve; - vector<double> v_se_pve; - vector<double> v_traceG; - vector<double> v_beta; - vector<double> v_se_beta; - - double time_UtX; - double time_opt; - - // Main functions - void CopyFromParam (PARAM &cPar); - void CopyToParam (PARAM &cPar); - void CalcVChe (const gsl_matrix *K, const gsl_matrix *W, const gsl_vector *y); - void CalcVCreml (const gsl_matrix *K, const gsl_matrix *W, const gsl_vector *y); -}; - -#endif - - |