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Copy pathSingleTraitMCMCSamplingRoutines.c
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SingleTraitMCMCSamplingRoutines.c
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// QTLBIM - QTL Bayesian Interval Mapping
// Functions relevant to single trait analyses
//********************************************************************
#include "GlobalVars.h"
#include "GlobalVars_SingleTrait.h"
#include "StatUtils.h"
#include "SingleTraitMCMCSamplingRoutines.h"
#include <R.h>
#include <Rmath.h>
#include <R_ext/Random.h>
#include <R_ext/Utils.h>
#include <stdio.h>
#include <math.h>
/// Calculate the likelihood for categorical trait
double Likelihood(double *p,double *G)
{
double CC[CN+1], AL=0.0; int I,J;
for(I=0;I<NS;I++)
{
for(J=0;J<=CN;J++) CC[J]=NormalFunction((p[J]-AMU-G[I])/sqrt(VE[I]));
double T=0.0;
for(J=1;J<=CN;J++) T=T+(W[I]==(J-1))*(CC[J]-CC[J-1]);
AL=AL+log(T+1e-20);
}
return(AL);
}
// global variables - Cross,X.
///Transfering genotypes to regression coefficients
void Coefficient(int GENOTYPE) //UPDATEGENO=1
{
int K;
if(GROUP==1)
{
for(K=0;K<NG;K++) X[K]=(GENOTYPE==K)*1.0;
}
if(GROUP==0)
{
if(CROSS==2) //Cockerham model
{
X[0]=GENOTYPE-1.0,
X[1]=GENOTYPE*(2.0-GENOTYPE)-0.5;
}
else X[0]=GENOTYPE-0.5;
}
return;
}
void Coefficient0(int I,int L,int QL) //UPDATEGENO=0
{
int K;
if(GROUP==1)
{
for(K=0;K<NG;K++) X[K]=QPROB[QCHR[L]][I][QL][K];
}
if(GROUP==0)
{
if(CROSS==2) //Cockerham model
{
X[0]=QPROB[QCHR[L]][I][QL][2]-QPROB[QCHR[L]][I][QL][0],
X[1]=0.5*(QPROB[QCHR[L]][I][QL][1]-QPROB[QCHR[L]][I][QL][0]-QPROB[QCHR[L]][I][QL][2]);
}
else X[0]=0.5*(QPROB[QCHR[L]][I][QL][1]-QPROB[QCHR[L]][I][QL][0]);
}
return;
}
//global variables - GAMMA *
///Deleting QTL with all 0 effects
void ZeroEffect1(int L)
{
int L0;
GAMMA[L]=(GAMMA_MAIN[L]!=0);
if(EPISTASIS==1)
{
for(L0=0;L0<=L-1;L0++) GAMMA[L]=GAMMA[L]+(GAMMA_EPISTASIS[L0][L]!=0);
for(L0=L+1;L0<NQTL;L0++) GAMMA[L]=GAMMA[L]+(GAMMA_EPISTASIS[L][L0]!=0);
}
if(GBYE==1)
{
for(L0=0;L0<NFIXCOVA;L0++)
if(GBYE_FIX_INDEX[L0]==1) GAMMA[L]=GAMMA[L]+(GAMMA_GBYE[L0][L]!=0);
}
return;
}
//global variables - GAMMA *
void ZeroEffect2(int L1, int L2)
{
int L0;
GAMMA[L1]=(GAMMA_MAIN[L1]!=0);
GAMMA[L2]=(GAMMA_MAIN[L2]!=0);
if(EPISTASIS==1)
{
for(L0=0;L0<=L1-1;L0++) GAMMA[L1]=GAMMA[L1]+(GAMMA_EPISTASIS[L0][L1]!=0);
for(L0=L1+1;L0<NQTL;L0++) GAMMA[L1]=GAMMA[L1]+(GAMMA_EPISTASIS[L1][L0]!=0);
for(L0=0;L0<=L2-1;L0++) GAMMA[L2]=GAMMA[L2]+(GAMMA_EPISTASIS[L0][L2]!=0);
for(L0=L2+1;L0<NQTL;L0++) GAMMA[L2]=GAMMA[L2]+(GAMMA_EPISTASIS[L2][L0]!=0);
}
if(GBYE==1)
{
for(L0=0;L0<NFIXCOVA;L0++)
if(GBYE_FIX_INDEX[L0]==1)
{
GAMMA[L1]=GAMMA[L1]+(GAMMA_GBYE[L0][L1]!=0);
GAMMA[L2]=GAMMA[L2]+(GAMMA_GBYE[L0][L2]!=0);
}
}
return;
}
/// Used for updating QTL genotypes and locations.
double GenotypeSampling(int I,int L,int II,int QL) //if UPDATEGENO==1(0), dosenot need QL(II)
{
int L1,K,K1,K2; double G;
if(UPDATEGENO==1) Coefficient(II);
if(UPDATEGENO==0) Coefficient0(I,L,QL);
G=GVALUE[I];
for(K=0;K<NC;K++) G=G-COEF[I][L][K]*MAIN[L][K]+X[K]*MAIN[L][K];
if(EPISTASIS==1)
for(L1=0;L1<NQTL;L1++)
{
if(L1<L&&GAMMA[L1]!=0&&GAMMA_EPISTASIS[L1][L]!=0)
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++)
G=G-COEF[I][L1][K1]*COEF[I][L][K2]*EPISTATIC[L1][L][K1][K2]+COEF[I][L1][K1]*X[K2]*EPISTATIC[L1][L][K1][K2];
if(L1>L&&GAMMA[L1]!=0&&GAMMA_EPISTASIS[L][L1]!=0)
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++)
G=G-COEF[I][L][K1]*COEF[I][L1][K2]*EPISTATIC[L][L1][K1][K2]+X[K1]*COEF[I][L1][K2]*EPISTATIC[L][L1][K1][K2];
}
if(GBYE==1)
for(L1=0;L1<NFIXCOVA;L1++)
if(GBYE_FIX_INDEX[L1]==1&&GAMMA_GBYE[L1][L]!=0)
for(K=0;K<NC;K++)
G=G-COEF_FIX[I][L1]*COEF[I][L][K]*GBYE_FIX[L1][L][K]+COEF_FIX[I][L1]*X[K]*GBYE_FIX[L1][L][K];
return(G);
}
/// Update the overall mean
void Mean(double YBAR,double VP) //prior for AMU is N(YBAR,VP)
{
int I; double T1=0.0,T2=0.0,T3,U,U0;
for(I=0;I<NS;I++)
{
T1=T1+(Y[I]-GVALUE[I])/VE[I];
T2=T2+1.0/VE[I];
}
T3=T2+1/VP;
ANORMAL(&U,&U0);
AMU=(T1+YBAR/VP)/T3+U/sqrt(T3);
return;
}
/// Update the residual variance
void ResidualVariance() //prior for VE is uniform
{
int I; double T1=0.0,T2=0.0,U,U0;
for(I=0;I<NS;I++)
{
T1=T1+pow(Y[I]-AMU-GVALUE[I],2);
ANORMAL(&U,&U0);
T2=T2+U*U;
}
for(I=0;I<NS;I++) VE[I]=T1/T2;
return;
}
/// Update the marginal effects
void MainEffect(int L,int K)
{
int I; double G[NS1],T1,T2,T3,U,U0;
T1=0,T2=0;
for(I=0;I<NS;I++)
{
double Z=COEF[I][L][K];
G[I]=GVALUE[I]-Z*MAIN[L][K];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+pow(Z,2)/VE[I];
}
double V=VMAIN[L][K];
if(GROUP==1) V=VMAIN1[L];
T3=1/V+T2;
ANORMAL(&U,&U0);
MAIN[L][K]=T1/T3+U/sqrt(T3);
for(I=0;I<NS;I++) GVALUE[I]=G[I]+COEF[I][L][K]*MAIN[L][K];
return;
}
/// Update the epistatic effects
void EpistaticEffect(int L1,int L2,int K1,int K2)
{
int I; double G[NS1],T1,T2,T3,U,U0;
T1=0,T2=0;
for(I=0;I<NS;I++)
{
double Z=COEF[I][L1][K1]*COEF[I][L2][K2];
G[I]=GVALUE[I]-Z*EPISTATIC[L1][L2][K1][K2];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+pow(Z,2)/VE[I];
}
double V=VEPISTASIS[L1][L2][K1][K2];
if(GROUP==1) V=VEPISTASIS1[L1][L2];
T3=1/V+T2;
ANORMAL(&U,&U0);
EPISTATIC[L1][L2][K1][K2]=T1/T3+U/sqrt(T3);
for(I=0;I<NS;I++) GVALUE[I]=G[I]+COEF[I][L1][K1]*COEF[I][L2][K2]*EPISTATIC[L1][L2][K1][K2];
return;
}
/// Update g by e fixed effects
void GBYE_FixedCovariate(int L1,int L2,int K)
{
int I; double G[NS1],T1,T2,T3,U,U0;
T1=0,T2=0;
for(I=0;I<NS;I++)
{
double Z=COEF_FIX[I][L1]*COEF[I][L2][K];
G[I]=GVALUE[I]-Z*GBYE_FIX[L1][L2][K];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+pow(Z,2)/VE[I];
}
double V=V_GBYE_FIX[L1][L2][K];
if(GROUP==1) V=V_GBYE_FIX1[L1][L2];
T3=1/V+T2;
ANORMAL(&U,&U0);
GBYE_FIX[L1][L2][K]=T1/T3+U/sqrt(T3);
for(I=0;I<NS;I++) GVALUE[I]=G[I]+COEF_FIX[I][L1]*COEF[I][L2][K]*GBYE_FIX[L1][L2][K];
return;
}
/// Updating genetic variances
void MainVariance(int L,int K,int NU,double TAU) //prior for VMAIN is Inv-chisq(NU,(NU-2)/NU*TAU),E(VMAIN)=TAU
{
int J; double T1,T2,U,U0;
T1=pow(MAIN[L][K],2);
T2=0;
for(J=0;J<1+NU;J++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
VMAIN[L][K]=(T1+NU*TAU)/T2;
return;
}
void MainVariance1(int L,int NU,double TAU) //prior for VMAIN is Inv-chisq(NU,(NU-2)/NU*TAU),E(VMAIN)=TAU
{
int K,J; double T1,T2,U,U0;
T1=0,T2=0;
for(K=0;K<NC;K++) T1=T1+pow(MAIN[L][K],2);
int N_MAIN=NC;
for(J=0;J<N_MAIN+NU;J++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
VMAIN1[L]=(T1+NU*TAU)/T2;
return;
}
void EpistaticVariance(int L1,int L2,int K1,int K2,int NU,double TAU) //prior for VEPISTASIS is Inv-chisq(NU,(NU-2)/NU*TAU),E(VEPISTASIS)=TAU
{
int J;double T1,T2,U,U0;
T1=pow(EPISTATIC[L1][L2][K1][K2],2);
T2=0;
for(J=0;J<1+NU;J++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
VEPISTASIS[L1][L2][K1][K2]=(T1+NU*TAU)/T2;
return;
}
void EpistaticVariance1(int L1,int L2,int NU,double TAU) //prior for VEPISTASIS is Inv-chisq(NU,(NU-2)/NU*TAU),E(VEPISTASIS)=TAU
{
int K1,K2,J;double T1,T2,U,U0;
T1=0,T2=0;
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) T1=T1+pow(EPISTATIC[L1][L2][K1][K2],2);
int N_EPIS=NC*NC;
for(J=0;J<N_EPIS+NU;J++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
VEPISTASIS1[L1][L2]=(T1+NU*TAU)/T2;
return;
}
/// Updating genetic variances
void GBYE_FixedCovariate_Variance(int L1,int L2,int K,int NU,double TAU) //prior for V_GBYE is Inv-chisq(NU,(NU-2)/NU*TAU),E(V_GBYE)=TAU
{
int J; double T1,T2,U,U0;
T1=pow(GBYE_FIX[L1][L2][K],2);
T2=0;
for(J=0;J<1+NU;J++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
V_GBYE_FIX[L1][L2][K]=(T1+NU*TAU)/T2;
return;
}
void GBYE_FixedCovariate_Variance1(int L1,int L2,int NU,double TAU) //prior for V_GBYE is Inv-chisq(NU,(NU-2)/NU*TAU),E(V_GBYE)=TAU
{
int K,J; double T1,T2,U,U0;
T1=0,T2=0;
for(K=0;K<NC;K++) T1=T1+pow(GBYE_FIX[L1][L2][K],2);
int N_GBYE=NC;
for(J=0;J<N_GBYE+NU;J++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
V_GBYE_FIX1[L1][L2]=(T1+NU*TAU)/T2;
return;
}
/// Update nongenetic effects
void FixedCovariate(int L)
{
int I; double G[NS1],Z,T1=0.0,T2=0.0,T3,U,U0;
for(I=0;I<NS;I++)
{
Z=COEF_FIX[I][L];
G[I]=GVALUE[I]-Z*FIX[L];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+Z*Z/VE[I];
}
T3=T2; //prior is uniform
ANORMAL(&U,&U0);
FIX[L]=T1/T3+U/sqrt(T3);
for(I=0;I<NS;I++) GVALUE[I]=G[I]+COEF_FIX[I][L]*FIX[L];
return;
}
///
void RandomCovariate(int L)
{
int I,K; double G[NS1],T1,T2,T3,U,U0;
for(I=0;I<NS;I++) G[I]=GVALUE[I]-RAN[L][(int)COEF_RAN[I][L]];
for(K=0;K<NRAN[L];K++)
{
T1=0,T2=0;
for(I=0;I<NS;I++)
if(COEF_RAN[I][L]==K)
{
T1=T1+(Y[I]-AMU-G[I])/VE[I];
T2=T2+1.0/VE[I];
}
T3=1/VRAN[L]+T2;
ANORMAL(&U,&U0);
RAN[L][K]=T1/T3+U/sqrt(T3);
}
for(I=0;I<NS;I++) GVALUE[I]=G[I]+RAN[L][(int)COEF_RAN[I][L]];
return;
}
///
void RanVariance(int L) //prior is uniform
{
int K; double T1=0,T2=0,U,U0;
for(K=0;K<NRAN[L];K++) T1=T1+pow(RAN[L][K],2);
for(K=0;K<NRAN[L]-1;K++)
{
ANORMAL(&U,&U0);
T2=T2+U*U;
}
VRAN[L]=T1/T2; //see Gelman P301
return;
}
/// Update QTL genotypes : generate IBD
void QTLgenotype(int L,int NL,int QL,int I)
{
int K; double SUMM[NG];
for(K=0;K<NG;K++) SUMM[K]=GenotypeSampling(I,L,K,QL);
double SUM=0.0;
for(K=0;K<NG;K++)
{
SUMM[K]=exp(-0.5*pow(Y[I]-(AMU+SUMM[K]),2)/VE[I])*QPROB[NL][I][QL][K];
SUM=SUM+SUMM[K];
}
for(K=0;K<NG;K++) SUMM[K]=SUMM[K]/SUM;
MULTINORMAL(SUMM);
PDD1=0.0,PDD2=0.0;
for(K=0;K<NG;K++)
{
PDD1=PDD1+QPROB[NL][I][QL][K]*(IBD==K);
PDD2=PDD2+SUMM[K]*(IBD==K);
}
return;
}
/// Update the positions of the QTLs
void QTLPOSITION(int L,int QLNEW)
{
int I,GENO1[NS1],K; double G[NS1];
double PROB0=0.0,PROB1=0.0,PD10=0.0,PD20=0.0;
for(I=0;I<NS;I++)
{
G[I]=GVALUE[I];
if(UPDATEGENO==1)
{
int KK=0;
for(K=0;K<NG;K++)
if(QPROB[QCHR[L]][I][QLNEW][K]>0.99)
{
GENO1[I]=K;
KK=1;
}
if(KK==0)
{
QTLgenotype(L,QCHR[L],QLNEW,I);
PD10=PD10+log(PDD1+1e-20);
PD20=PD20+log(PDD2+1e-20);
GENO1[I]=IBD;
}
if(GENO[I][L]!=GENO1[I])
{
int II=GENO1[I];
G[I]=GenotypeSampling(I,L,II,QLNEW); //QLNEW is not used
}
}
if(UPDATEGENO==0) G[I]=GenotypeSampling(I,L,0,QLNEW); //0 is not used
if(G[I]!=GVALUE[I])
{
PROB0=PROB0-0.5*pow(Y[I]-AMU-GVALUE[I],2)/VE[I];
PROB1=PROB1-0.5*pow(Y[I]-AMU-G[I],2)/VE[I];
}
}
double S1=(PROB1-PROB0)+(PD10-PD1[L])+(PD2[L]-PD20);
if(S1>log(RANDOM()))
{
QLOC[L]=QLNEW;
for(I=0;I<NS;I++)
{
GVALUE[I]=G[I];
if(UPDATEGENO==1)
{
GENO[I][L]=GENO1[I];
Coefficient(GENO1[I]);
}
if(UPDATEGENO==0) Coefficient0(I,L,QLOC[L]);
for(K=0;K<NC;K++) COEF[I][L][K]=X[K];
}
PD1[L]=PD10,PD2[L]=PD20;
}
return;
}
/// Sampling a position
int SamplingOnePosition(int L)
{
int NL,I,K,CHR0[NLG],T,TT,TTT,GRID00[TNGRID]; double R,GRID0[TNGRID];
for(I=0;I<NLG;I++)
{
CHRQTL[I]=0;
for(K=0;K<NQTL;K++) CHRQTL[I]=CHRQTL[I]+(QCHR[K]==I&&GAMMA[K]!=0);
}
T=0;
for(I=0;I<NLG;I++)
{
if(GRID[I][NGRID[I]-1]!=0&&DQQ[I]!=0)
CHR0[I]=NGRID[I]-(int)(2*DQQ[I]*CHRQTL[I]*NGRID[I]/GRID[I][NGRID[I]-1]);
if(DQQ[I]==0) CHR0[I]=NGRID[I]-CHRQTL[I];
if(GRID[I][NGRID[I]-1]==0) CHR0[I]=0;
if(CHRQTL[I]>=CHR_NQTL[I]||CHR0[I]<=0) CHR0[I]=0;
T=T+CHR0[I];
}
if(T!=0)
{
R=T*RANDOM();
TT=0;
for(I=0;I<NLG;I++)
{
if(R>=TT&&R<(TT+CHR0[I])) QCHR[L]=I;
TT=TT+CHR0[I];
}
NL=QCHR[L];
if(CHRQTL[NL]+1>CHR_NQTL[NL]||CHR0[NL]==0) T=0;
}
if(T!=0)
{
if(CHRQTL[NL]==0) QLOC[L]=(int)(RANDOM()*NGRID[NL]);
if(CHRQTL[NL]>0)
{
TT=0;
for(K=0;K<NQTL;K++)
if(QCHR[K]==NL&&GAMMA[K]!=0)
{
GRID0[TT]=GRID[NL][QLOC[K]];
TT=TT+1;
}
QLOC[L]=(int)(RANDOM()*NGRID[NL]);
TT=0;
for(K=0;K<CHRQTL[NL];K++)
if(fabs(GRID[NL][QLOC[L]]-GRID0[K])<=DQQ[NL]) TT=TT+1;
if(TT!=0)
{
TTT=0;
for(I=0;I<NGRID[NL];I++)
{
GRID00[I]=1;
for(K=0;K<CHRQTL[NL];K++)
if(fabs(GRID[NL][I]-GRID0[K])<=DQQ[NL]) GRID00[I]=0;
TTT=TTT+GRID00[I];
}
if(TTT!=0)
{
R=RANDOM()*TTT;
TT=0;
for(I=0;I<NGRID[NL];I++)
{
if(R>=TT&&R<(TT+GRID00[I])) QLOC[L]=I;
TT=TT+GRID00[I];
}
}
if(TTT==0) T=0;
}
for(K=0;K<CHRQTL[NL];K++)
if(fabs(GRID[NL][QLOC[L]]-GRID0[K])<=DQQ[NL]) T=0;
}
}
if(T!=0)
{
for(I=0;I<NS;I++)
{
if(UPDATEGENO==1)
{
double PRR[NG];
for(K=0;K<NG;K++) PRR[K]=QPROB[NL][I][QLOC[L]][K];
MULTINORMAL(PRR);
GENO[I][L]=IBD;
Coefficient(IBD);
}
if(UPDATEGENO==0) Coefficient0(I,L,QLOC[L]);
for(K=0;K<NC;K++) COEF[I][L][K]=X[K];
}
}
return(T);
}
/// Update main effect indicators
void MainEffectIndicator_GROUP0(int L,int K)
{
int I,K1;
double G[NS1],BF_10,GAMMA_1=-(1e+100),GAMMA_0=-(1e+100),T1=0,T2=0,T3,F1=0,F2=0;
for(I=0;I<NS;I++)
{
double Z=COEF[I][L][K];
G[I]=GVALUE[I]-Z*MAIN[L][K];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+Z*Z/VE[I];
}
T3=1/VMAIN[L][K]+T2;
for(I=0;I<NS;I++)
{
double Z=COEF[I][L][K];
F1=F1+pow(Y[I]-AMU-G[I],2)/VE[I];
F2=F2+pow(Y[I]-AMU-G[I]-Z*T1/T3,2)/VE[I];
}
BF_10=-0.5*log(VMAIN[L][K])-0.5*pow(T1/T3,2)/VMAIN[L][K]-0.5*log(T3);
BF_10=-0.5*F2+0.5*F1+BF_10;
if(MAIN[L][K]==0) GAMMA_1=BF_10;
if(MAIN[L][K]!=0) GAMMA_0=-BF_10;
double R=log(RANDOM());
if(MAIN[L][K]==0&&R<GAMMA_1)
{
double U,U0;
ANORMAL(&U,&U0);
MAIN[L][K]=T1/T3+U/sqrt(T3);
GAMMA_MAIN[L]=1;
GAMMA[L]=1;
for(I=0;I<NS;I++) GVALUE[I]=G[I]+COEF[I][L][K]*MAIN[L][K];
}
if(MAIN[L][K]!=0&&R<GAMMA_0)
{
MAIN[L][K]=0;
double SUM=0;
for(K1=0;K1<NC;K1++) SUM=SUM+fabs(MAIN[L][K1]);
if(SUM==0)
{
GAMMA_MAIN[L]=0;
ZeroEffect1(L);
}
for(I=0;I<NS;I++) GVALUE[I]=G[I];
}
return;
}
///
void MainEffectIndicator_GROUP1(int L)
{
int I,K;
double G[NS1],BF_10,GAMMA_1=-(1e+100),GAMMA_0=-(1e+100),T1[NG],T2[NG],T3[NG],F1=0,F2=0;
for(I=0;I<NG;I++)
{
T1[I]=0, T2[I]=0, T3[I]=0;
}
for(I=0;I<NS;I++)
{
G[I]=GVALUE[I];
for(K=0;K<NC;K++) G[I]=G[I]-COEF[I][L][K]*MAIN[L][K];
}
for(K=0;K<NC;K++)
{
for(I=0;I<NS;I++)
{
double Z=COEF[I][L][K];
T1[K]=T1[K]+Z*(Y[I]-AMU-G[I])/VE[I];
T2[K]=T2[K]+Z*Z/VE[I];
}
T3[K]=1/VMAIN1[L]+T2[K];
}
for(I=0;I<NS;I++)
{
F1=F1+pow(Y[I]-AMU-G[I],2)/VE[I];
double F3=0;
for(K=0;K<NC;K++) F3=F3+COEF[I][L][K]*T1[K]/T3[K];
F2=F2+pow(Y[I]-AMU-G[I]-F3,2)/VE[I];
}
BF_10=0;
for(K=0;K<NC;K++) BF_10=BF_10-0.5*log(VMAIN1[L])-0.5*pow(T1[K]/T3[K],2)/VMAIN1[L]-0.5*log(T3[K]);
BF_10=-0.5*F2+0.5*F1+BF_10;
if(GAMMA_MAIN[L]==0) GAMMA_1=BF_10;
if(GAMMA_MAIN[L]!=0) GAMMA_0=-BF_10;
double R=log(RANDOM());
if(GAMMA_MAIN[L]==0&&R<GAMMA_1)
{
for(K=0;K<NC;K++)
{
double U,U0;
ANORMAL(&U,&U0);
MAIN[L][K]=T1[K]/T3[K]+U/sqrt(T3[K]);
}
GAMMA_MAIN[L]=1;
GAMMA[L]=1;
for(I=0;I<NS;I++)
{
GVALUE[I]=G[I];
for(K=0;K<NC;K++) GVALUE[I]=GVALUE[I]+COEF[I][L][K]*MAIN[L][K];
}
}
if(GAMMA_MAIN[L]!=0&&R<GAMMA_0)
{
for(K=0;K<NC;K++) MAIN[L][K]=0;
GAMMA_MAIN[L]=0;
for(I=0;I<NS;I++) GVALUE[I]=G[I];
ZeroEffect1(L);
}
return;
}
/// Update epistatic effect indicators
void EpistasisIndicator_GROUP0(int L1,int L2,int K1,int K2)
{
int I,K01,K02;
double G[NS1],BF_10,GAMMA_1=-(1e+100),GAMMA_0=-(1e+100),T1=0,T2=0,T3,F1=0,F2=0;
if(W_EPISTASIS!=0)
{
for(I=0;I<NS;I++)
{
double Z=COEF[I][L1][K1]*COEF[I][L2][K2];
G[I]=GVALUE[I]-Z*EPISTATIC[L1][L2][K1][K2];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+Z*Z/VE[I];
}
T3=1/VEPISTASIS[L1][L2][K1][K2]+T2;
for(I=0;I<NS;I++)
{
double Z=COEF[I][L1][K1]*COEF[I][L2][K2];
F1=F1+pow(Y[I]-AMU-G[I],2)/VE[I];
F2=F2+pow(Y[I]-AMU-G[I]-Z*T1/T3,2)/VE[I];
}
BF_10=-0.5*log(VEPISTASIS[L1][L2][K1][K2])-0.5*pow(T1/T3,2)/VEPISTASIS[L1][L2][K1][K2]-0.5*log(T3);
BF_10=-0.5*F2+0.5*F1+BF_10;
if(EPISTATIC[L1][L2][K1][K2]==0) GAMMA_1=BF_10;
if(EPISTATIC[L1][L2][K1][K2]!=0) GAMMA_0=-BF_10;
double R=log(RANDOM());
if(EPISTATIC[L1][L2][K1][K2]==0&&R<GAMMA_1)
{
double U,U0;
ANORMAL(&U,&U0);
EPISTATIC[L1][L2][K1][K2]=T1/T3+U/sqrt(T3);
GAMMA_EPISTASIS[L1][L2]=1;
GAMMA[L1]=1,GAMMA[L2]=1;
for(I=0;I<NS;I++) GVALUE[I]=G[I]+COEF[I][L1][K1]*COEF[I][L2][K2]*EPISTATIC[L1][L2][K1][K2];
}
if(EPISTATIC[L1][L2][K1][K2]!=0&&R<GAMMA_0)
{
EPISTATIC[L1][L2][K1][K2]=0;
double SUM=0;
for(K01=0;K01<NC;K01++)
for(K02=0;K02<NC;K02++) SUM=SUM+fabs(EPISTATIC[L1][L2][K01][K02]);
if(SUM==0)
{
GAMMA_EPISTASIS[L1][L2]=0;
ZeroEffect2(L1,L2);
}
for(I=0;I<NS;I++) GVALUE[I]=G[I];
}
}
if(W_EPISTASIS==0&&EPISTATIC[L1][L2][K1][K2]!=0)
{
for(I=0;I<NS;I++) GVALUE[I]=GVALUE[I]-COEF[I][L1][K1]*COEF[I][L2][K2]*EPISTATIC[L1][L2][K1][K2];
EPISTATIC[L1][L2][K1][K2]=0;
double SUM=0;
for(K01=0;K01<NC;K01++)
for(K02=0;K02<NC;K02++) SUM=SUM+fabs(EPISTATIC[L1][L2][K01][K02]);
if(SUM==0)
{
GAMMA_EPISTASIS[L1][L2]=0;
ZeroEffect2(L1,L2);
}
}
return;
}
///
void EpistasisIndicator_GROUP1(int L1,int L2)
{
int I,K1,K2;
double G[NS1],BF_10,GAMMA_1=-(1e+100),GAMMA_0=-(1e+100),T1[NG][NG],T2[NG][NG],T3[NG][NG],F1=0,F2=0;
if(W_EPISTASIS!=0)
{
for(K1=0;K1<NG;K1++)
for(K2=0;K2<NG;K2++)
{
T1[K1][K2]=0, T2[K1][K2]=0, T3[K1][K2]=0;
}
for(I=0;I<NS;I++)
{
G[I]=GVALUE[I];
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) G[I]=G[I]-COEF[I][L1][K1]*COEF[I][L2][K2]*EPISTATIC[L1][L2][K1][K2];
}
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++)
{
for(I=0;I<NS;I++)
{
double Z=COEF[I][L1][K1]*COEF[I][L2][K2];
T1[K1][K2]=T1[K1][K2]+Z*(Y[I]-AMU-G[I])/VE[I];
T2[K1][K2]=T2[K1][K2]+Z*Z/VE[I];
}
T3[K1][K2]=1/VEPISTASIS1[L1][L2]+T2[K1][K2];
}
for(I=0;I<NS;I++)
{
F1=F1+pow(Y[I]-AMU-G[I],2)/VE[I];
double F3=0;
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) F3=F3+COEF[I][L1][K1]*COEF[I][L2][K2]*T1[K1][K2]/T3[K1][K2];
F2=F2+pow(Y[I]-AMU-G[I]-F3,2)/VE[I];
}
BF_10=0;
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++)
BF_10=BF_10-0.5*log(VEPISTASIS1[L1][L2])-0.5*pow(T1[K1][K2]/T3[K1][K2],2)/VEPISTASIS1[L1][L2]-0.5*log(T3[K1][K2]);
BF_10=-0.5*F2+0.5*F1+BF_10;
if(GAMMA_EPISTASIS[L1][L2]==0) GAMMA_1=BF_10;
if(GAMMA_EPISTASIS[L1][L2]!=0) GAMMA_0=-BF_10;
double R=log(RANDOM());
if(GAMMA_EPISTASIS[L1][L2]==0&&R<GAMMA_1)
{
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++)
{
double U,U0;
ANORMAL(&U,&U0);
EPISTATIC[L1][L2][K1][K2]=T1[K1][K2]/T3[K1][K2]+U/sqrt(T3[K1][K2]);
}
GAMMA_EPISTASIS[L1][L2]=1;
GAMMA[L1]=1,GAMMA[L2]=1;
for(I=0;I<NS;I++)
{
GVALUE[I]=G[I];
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) GVALUE[I]=GVALUE[I]+COEF[I][L1][K1]*COEF[I][L2][K2]*EPISTATIC[L1][L2][K1][K2];
}
}
if(GAMMA_EPISTASIS[L1][L2]!=0&&R<GAMMA_0)
{
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) EPISTATIC[L1][L2][K1][K2]=0;
GAMMA_EPISTASIS[L1][L2]=0;
for(I=0;I<NS;I++) GVALUE[I]=G[I];
ZeroEffect2(L1,L2);
}
}
if(W_EPISTASIS==0&&GAMMA_EPISTASIS[L1][L2]!=0)
{
for(I=0;I<NS;I++)
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) GVALUE[I]=GVALUE[I]-COEF[I][L1][K1]*COEF[I][L2][K2]*EPISTATIC[L1][L2][K1][K2];
for(K1=0;K1<NC;K1++)
for(K2=0;K2<NC;K2++) EPISTATIC[L1][L2][K1][K2]=0;
GAMMA_EPISTASIS[L1][L2]=0;
ZeroEffect2(L1,L2);
}
return;
}
/// Update g by e fixed effect indicators
void GBYE_FIX_Indicator_GROUP0(int L1,int L2,int K) //use the constraint model
{
int I,K1;
double G[NS1],BF_10,GAMMA_1=-(1e+100),GAMMA_0=-(1e+100),T1=0,T2=0,T3,F1=0,F2=0;
for(I=0;I<NS;I++)
{
double Z=COEF_FIX[I][L1]*COEF[I][L2][K];
G[I]=GVALUE[I]-Z*GBYE_FIX[L1][L2][K];
T1=T1+Z*(Y[I]-AMU-G[I])/VE[I];
T2=T2+Z*Z/VE[I];
}
T3=1/V_GBYE_FIX[L1][L2][K]+T2;
for(I=0;I<NS;I++)
{
double Z=COEF_FIX[I][L1]*COEF[I][L2][K];
F1=F1+pow(Y[I]-AMU-G[I],2)/VE[I];