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Diffstat (limited to 'param.cpp')
| -rw-r--r-- | param.cpp | 849 |
1 files changed, 0 insertions, 849 deletions
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; -} - - - |