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authorxiangzhou2014-09-20 10:17:34 -0400
committerxiangzhou2014-09-20 10:17:34 -0400
commit17deca2d54827a00df3ea4d98df700fc2b8ed777 (patch)
tree7e63a05c61c3c33d425b5642aa8f9df38717d1f8 /lm.cpp
downloadpangemma-17deca2d54827a00df3ea4d98df700fc2b8ed777.tar.gz
initial upload, version 0.95alpha
Diffstat (limited to 'lm.cpp')
-rw-r--r--lm.cpp571
1 files changed, 571 insertions, 0 deletions
diff --git a/lm.cpp b/lm.cpp
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--- /dev/null
+++ b/lm.cpp
@@ -0,0 +1,571 @@
+/*
+ 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;
+	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="./output/"+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;
+}