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-/*
- 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;
-}
-
-
-
generated by cgit v1.2.3 (git 2.47.1) at 2025-03-15 02:49:52 +0000