R/mrMLMFun.R

In mrMLM.GUI: Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for Genome-Wide Association Study with Graphical User Interface

mrMLMFun<-function(gen,phe,outATCG,genRaw,kk,psmatrix,svpal,svrad,svmlod,Genformat,CLO){

inputform<-Genformat

if(is.null(kk)){
  if(is.null(gen)==TRUE)
  {
    showModal(modalDialog(title = "Warning", strong("Please input correct genotypic dataset !"), easyClose = TRUE))
  }else{
    envgenq<-deepcopy(gen,3:ncol(gen))
    envgenq2<-t(envgenq[,])
    # envgen<-big.matrix(nrow(envgenq2),ncol(envgenq2),type='double',shared = FALSE)
    # envgen[,]<-envgenq2[,]
    rm(envgenq)
    gc()
    
    # m<-ncol(envgen)
    # n<-nrow(envgen)
    #kk1<-matrix(0,n,n)
    # for(k in 1:m){
    #   z<-as.matrix(envgen[,k])
    #   kk1<-kk1+z%*%t(z)
    # }
    kk1<-mrMLM.GUI::multiplication_speed(envgenq2,t(envgenq2))
    cc<-mean(diag(kk1))
    kk1<-kk1/cc
    kk<-as.matrix(kk1)
  }
  rm(kk1)
  gc()
} 

if(is.null(psmatrix)){
  flagps<-1
}else{
  flagps<-0
}

if(is.null(svrad)==TRUE||is.null(svmlod)==TRUE){
  showModal(modalDialog(title = "Warning", strong("Please set parameters!"), easyClose = TRUE))
}
if(svrad<0)
{
  showModal(modalDialog(title = "Warning", strong("Please input search radius (kb) of candidate gene: > 0 !"), easyClose = TRUE))
}
if(svmlod<0)
{
  showModal(modalDialog(title = "Warning", strong("Please input critical LOD score: > 0 !"), easyClose = TRUE))
}
if(exists("gen")==FALSE)
{
  showModal(modalDialog(title = "Warning", strong("Please input correct genotypic dataset!"), easyClose = TRUE))
}
if(exists("phe")==FALSE)
{
  showModal(modalDialog(title = "Warning", strong("Please input correct phenotypic dataset !"), easyClose = TRUE))
}
if(exists("kk")==FALSE)
{
  showModal(modalDialog(title = "Warning", strong("Please input correct kinship (K) dataset !"), easyClose = TRUE))
}
if((exists("gen")==TRUE)&&(exists("phe")==TRUE)&&(ncol(gen)!=(nrow(phe)+2)))
{
  showModal(modalDialog(title = "Warning", strong("Sample size in genotypic dataset doesn't equal to the sample size in phenotypic dataset !"), easyClose = TRUE))
}

if((exists("gen")==TRUE)&&(exists("phe")==TRUE)&&(exists("kk")==TRUE)&&((ncol(gen)==(nrow(phe)+2)))&&(svrad>0)&&(svmlod>=0))
{
parmsShow<-NULL
wan<-NULL
parms<-NULL
parms.pchange<-NULL
mannewp<-NULL

multinormal<-function(y,mean,sigma)
{
  pdf_value<-(1/sqrt(2*3.14159265358979323846*sigma))*exp(-(y-mean)*(y-mean)/(2*sigma));
  return (pdf_value)
}

ebayes_EM<-function(x,z,y)
{
  n<-nrow(z);k<-ncol(z)
  
  if(abs(min(eigen(crossprod(x,x))$values))<1e-6){
    b<-solve(crossprod(x,x)+diag(ncol(x))*1e-8)%*%crossprod(x,y)
  }else{
    b<-solve(crossprod(x,x))%*%(crossprod(x,y))
  }
  
  v0<-as.numeric(crossprod((y-x%*%b),(y-x%*%b))/n)
  u<-matrix(rep(0,k),k,1)
  v<-matrix(rep(0,k),k,1)
  s<-matrix(rep(0,k),k,1)
  for(i in 1:k)
  {
    zz<-z[,i]
    s[i]<-((crossprod(zz,zz)+1e-100)^(-1))*v0
    u[i]<-s[i]*crossprod(zz,(y-x%*%b))/v0
    v[i]<-u[i]^2+s[i]
  }
  
  vv<-matrix(rep(0,n*n),n,n);
  for(i in 1:k)
  {
    zz<-z[,i]
    vv=vv+tcrossprod(zz,zz)*v[i]
  }
  vv<-vv+diag(n)*v0
  
  iter<-0;err<-1000;iter_max<-500;err_max<-1e-8
  tau<-0;omega<-0
  while((iter<iter_max)&&(err>err_max))
  {
    iter<-iter+1
    v01<-v0
    v1<-v
    b1<-b
    vi<-solve(vv)
    xtv<-crossprod(x,vi)
    
    if(ncol(x)==1)
    {
      b<-((xtv%*%x)^(-1))*(xtv%*%y)
    }else{
      if(abs(min(eigen(xtv%*%x)$values))<1e-6){
        b<-solve((xtv%*%x)+diag(ncol(x))*1e-8)%*%(xtv%*%y)
      }else{
        b<-solve(xtv%*%x)%*%(xtv%*%y)
      }
    }
    r<-y-x%*%b
    ss<-matrix(rep(0,n),n,1)
    for(i in 1:k)
    {
      zz<-z[,i]
      zztvi<-crossprod(zz,vi)
      u[i]<-v[i]*zztvi%*%r
      s[i]<-v[i]*(1-zztvi%*%zz*v[i])
      v[i]<-(u[i]^2+s[i]+omega)/(tau+3)
      ss<-ss+zz*u[i]
    }
    v0<-as.numeric(crossprod(r,(r-ss))/n)
    
    vv<-matrix(rep(0,n*n),n,n)
    for(i in 1:k)
    {
      zz<-z[,i]
      vv<-vv+tcrossprod(zz,zz)*v[i]
    }
    vv<-vv+diag(n)*v0
    
    err<-(crossprod((b1-b),(b1-b))+(v01-v0)^2+crossprod((v1-v),(v1-v)))/(2+k)
    beta<-t(b)
    sigma2<-v0
  }
  
  wang<-matrix(rep(0,k),k,1)
  for (i in 1:k){
    stderr<-sqrt(s[i]+1e-20)
    t<-abs(u[i])/stderr
    f<-t*t
    p<-pchisq(f,1,lower.tail = F)
    wang[i]<-p
  }
  
  return(list(u=u,sigma2=sigma2,wang=wang))
}

likelihood<-function(xxn,xxx,yn,bbo)
{
  nq<-ncol(xxx)
  ns<-nrow(yn)
  at1<-0
  
  if(is.null(bbo)==TRUE){
    ww1<-1:ncol(xxx)
    ww1<-as.matrix(ww1)
  }else{
    ww1<-as.matrix(which(abs(bbo)>1e-5))
  }
  at1<-dim(ww1)[1]
  lod<-matrix(rep(0,nq),nq,1)
  if(at1>0.5)
    ad<-cbind(xxn,xxx[,ww1])
  else
    ad<-xxn
  if(abs(min(eigen(crossprod(ad,ad))$values))<1e-6)
    bb<-solve(crossprod(ad,ad)+diag(ncol(ad))*0.01)%*%crossprod(ad,yn)
  else
    bb<-solve(crossprod(ad,ad))%*%crossprod(ad,yn)
  vv1<-as.numeric(crossprod((yn-ad%*%bb),(yn-ad%*%bb))/ns);
  ll1<-sum(log(abs(multinormal(yn,ad%*%bb,vv1))))
  sub<-1:ncol(ad);
  if(at1>0.5)
  {
    for(i in 1:at1)
    {
      ij<-which(sub!=sub[i+ncol(xxn)])
      ad1<-ad[,ij]
      if(abs(min(eigen(crossprod(ad1,ad1))$values))<1e-6)
        bb1<-solve(crossprod(ad1,ad1)+diag(ncol(ad1))*0.01)%*%crossprod(ad1,yn)
      else
        bb1<-solve(crossprod(ad1,ad1))%*%crossprod(ad1,yn) 
      vv0<-as.numeric(crossprod((yn-ad1%*%bb1),(yn-ad1%*%bb1))/ns);
      ll0<-sum(log(abs(multinormal(yn,ad1%*%bb1,vv0))))
      lod[ww1[i]]<--2.0*(ll0-ll1)/(2.0*log(10))
    }
  }
  return (lod)
}

mixed<-function(x,y,kk){
  
  loglike<-function(theta){
    lambda<-exp(theta)
    logdt<-sum(log(lambda*delta+1))
    h<-1/(lambda*delta+1)
    yy<-sum(yu*h*yu)
    yx<-matrix(0,q,1)
    xx<-matrix(0,q,q)
    for(i in 1:q){
      yx[i]<-sum(yu*h*xu[,i])
      for(j in 1:q){
        xx[i,j]<-sum(xu[,i]*h*xu[,j])
      }
    }
    loglike<- -0.5*logdt-0.5*(n-q)*log(yy-t(yx)%*%solve(xx)%*%yx)-0.5*log(det(xx))
    return(-loglike)
  }
  
  fixed<-function(lambda){
    h<-1/(lambda*delta+1)
    yy<-sum(yu*h*yu)
    yx<-matrix(0,q,1)
    xx<-matrix(0,q,q)
    for(i in 1:q){
      yx[i]<-sum(yu*h*xu[,i])
      for(j in 1:q){
        xx[i,j]<-sum(xu[,i]*h*xu[,j])
      }
    }
    beta<-solve(xx,yx)
    sigma2<-(yy-t(yx)%*%solve(xx)%*%yx)/(n-q)
    sigma2<-drop(sigma2)
    var<-diag(solve(xx)*sigma2)
    stderr<-sqrt(var)
    return(c(beta,stderr,sigma2))
  }
  
  qq<-eigen(kk)
  delta<-qq[[1]]
  uu<-qq[[2]]
  q<-ncol(x)
  n<-ncol(kk)
  vp<-var(y)
  yu<-t(uu)%*%y
  xu<-t(uu)%*%x
  theta<-0
  parm<-optim(par=theta,fn=loglike,hessian = TRUE,method="L-BFGS-B",lower=-50,upper=10)
  lambda<-exp(parm$par)
  conv<-parm$convergence
  fn1<-parm$value
  fn0<-loglike(-Inf)
  lrt<-2*(fn0-fn1)
  hess<-parm$hessian
  parmfix<-fixed(lambda)
  beta<-parmfix[1:q]
  stderr<-parmfix[(q+1):(2*q)]
  sigma2<-parmfix[2*q+1]
  lod<-lrt/4.61
  p_value<-pchisq(lrt,1,lower.tail = F)
  sigma2g<-lambda*sigma2
  goodness<-(vp-sigma2)/vp
  par<-data.frame(lrt,beta,stderr,sigma2,lambda,sigma2g,lod,p_value)
  return(par)
}

loglike<-function(theta){
  xi<-exp(theta)
  tmp0<-zz*xi+1
  tmp<-xi*solve(tmp0)
  yHy<-yy-t(zy)%*%tmp%*%zy
  yHx<-yx-zx%*%tmp%*%zy
  xHx<-xx-zx%*%tmp%*%t(zx)
  logdt2<-log(det(tmp0))
  loglike<- -0.5*logdt2-0.5*(n-s)*log(yHy-t(yHx)%*%solve(xHx)%*%yHx)-0.5*log(det(xHx))
  return(-loglike)
}

fixed<-function(xi){
  tmp0<-zz*xi+diag(1)
  tmp<-xi*solve(tmp0)
  yHy<-yy-t(zy)%*%tmp%*%zy
  yHx<-yx-zx%*%tmp%*%zy
  xHx<-xx-zx%*%tmp%*%t(zx)
  zHy<-zy-zz%*%tmp%*%zy
  zHx<-zx-zx%*%tmp%*%zz
  zHz<-zz-zz%*%tmp%*%zz
  beta<-solve(xHx,yHx)
  tmp2<-solve(xHx)
  sigma2<-(yHy-t(yHx)%*%tmp2%*%yHx)/(n-s)
  gamma<-xi*zHy-xi*t(zHx)%*%tmp2%*%yHx
  var<-abs((xi*diag(1)-xi*zHz*xi)*as.numeric(sigma2))
  stderr<-sqrt(diag(var))
  result<-list(gamma,stderr,beta,sigma2)
  return(result)
}

name<-gen[,1:2]
genq<-deepcopy(gen,3:ncol(gen))
genq2<-t(genq[,])
gen<-big.matrix(nrow(genq2),ncol(genq2),type='double',shared = FALSE)
gen[,]<-genq2[,]
rm(genq2)
gc()
n<-nrow(gen)
m<-ncol(gen)
if((flagps==1)||(exists("psmatrix")==FALSE))
{
  x<-matrix(1,n,1)
}else if(flagps==0)
{
  x<-cbind(matrix(1,n,1),psmatrix)
}
ll<-numeric()
s<-ncol(x)
kk<-as.matrix(kk)
qq<-eigen(kk)
delta<-qq[[1]]
uu<-qq[[2]]
xu<-t(uu)%*%x

rm(qq)
gc()

yy<-phe[,1]
y<-as.matrix(yy)
parm<-mixed(x=x,y=y,kk=kk)
lambda<-parm$lambda[1]
h<-1/(delta*lambda+1)
yu<-t(uu)%*%y
xx<-matrix(0,s,s)
for(i in 1:s){
  for(j in 1:s){
    xx[i,j]<-sum(xu[,i]*h*xu[,j])
  }
}
yy<-sum(yu*h*yu)
yx<-matrix(0,s,1)
for(i in 1:s){
  yx[i]<-sum(yu*h*xu[,i])
}

genf<-gen[,]

cl.cores <- detectCores()
if((cl.cores<=2)||(is.null(CLO)==FALSE)){
  cl.cores<-1
}else if(cl.cores>2){
  if(cl.cores>10){
    cl.cores<-10
  }else {  
    cl.cores <- detectCores()-1
  }
}   
cl <- makeCluster(cl.cores)
registerDoParallel(cl)

if((flagps==1)||(is.null("psmatrix")))
{
  k<-numeric()
  ff=foreach(k=1:m, .multicombine=TRUE, .combine = 'rbind')%dopar%
  {
    #browser()
    z<-as.matrix(genf[,k])
    zu<-t(uu)%*%z
    zy<-as.matrix(sum(yu*h*zu))
    zz<-as.matrix(sum(zu*h*zu))
    zx<-matrix(0,s,1)
    for(i in 1:s){
      zx[i]<-sum(xu[,i]*h*zu)
    }
    theta<-c(0)
    par<-optim(par=theta,fn=loglike,hessian = TRUE,method="L-BFGS-B",lower=-10,upper=10)
    xi<-exp(par$par)
    conv<-par$convergence
    fn1<-par$value
    hess<-par$hessian
    parmfix<-fixed(xi)
    gamma<-parmfix[[1]]
    stderr<-parmfix[[2]]
    
    beta<-parmfix[[3]]
    
    sigma2<-parmfix[[4]]
    lambda<-xi
    sigma2g<-lambda*sigma2
    fn0<-loglike(-Inf)
    lrt<-2*(fn0-fn1)
    p_lrt<-pchisq(lrt,1,lower.tail = F)
    wald<-(gamma/stderr)^2
    p_wald<-pchisq(wald,1,lower.tail = F)
    parm0<-c(1,name[k,1],name[k,2],beta,sigma2,sigma2g,gamma,stderr,wald,p_wald)
    
  }
  stopCluster(cl)
  
  ll<-rbind(ll,ff)
}else if(flagps==0){
  k<-numeric()
  ff=foreach(k=1:m, .multicombine=TRUE, .combine = 'rbind')%dopar%
  {
    #browser()
    z<-as.matrix(genf[,k])
    zu<-t(uu)%*%z
    zy<-as.matrix(sum(yu*h*zu))
    zz<-as.matrix(sum(zu*h*zu))
    zx<-matrix(0,s,1)
    for(i in 1:s){
      zx[i]<-sum(xu[,i]*h*zu)
    }
    theta<-c(0)
    par<-optim(par=theta,fn=loglike,hessian = TRUE,method="L-BFGS-B",lower=-10,upper=10)
    xi<-exp(par$par)
    conv<-par$convergence
    fn1<-par$value
    hess<-par$hessian
    parmfix<-fixed(xi)
    gamma<-parmfix[[1]]
    stderr<-parmfix[[2]]
    
    beta<-parmfix[[3]][1]
    
    sigma2<-parmfix[[4]]
    lambda<-xi
    sigma2g<-lambda*sigma2
    fn0<-loglike(-Inf)
    lrt<-2*(fn0-fn1)
    p_lrt<-pchisq(lrt,1,lower.tail = F)
    wald<-(gamma/stderr)^2
    p_wald<-pchisq(wald,1,lower.tail = F)
    parm0<-c(1,name[k,1],name[k,2],beta,sigma2,sigma2g,gamma,stderr,wald,p_wald)
    
  }
  stopCluster(cl)
  
  ll<-rbind(ll,ff)
}


rm(uu,kk,genf)
gc()

parms<-ll
parms<-matrix(parms,,10)

chr_pos<-parms[,2:3]
pfit<-which(parms[,10]<=(svpal))
pfit<-as.matrix(pfit)
pfitrow<-nrow(pfit)
no_p<-cbind((1:(nrow(parms))),parms[,10])
no_porder<-order(no_p[,2])
no_p<-no_p[no_porder,]
choose_orderp<-no_p[1:pfitrow,]
orderno<-no_p[1:pfitrow,1]
orderno<-as.matrix(orderno)
sigma2g_SNPerr<-cbind(parms[,6],parms[,8])
correct_each<-matrix(1,(nrow(sigma2g_SNPerr)),1)-sigma2g_SNPerr[,2]*sigma2g_SNPerr[,2]/sigma2g_SNPerr[,1]
k0<-which(correct_each<0)
k0<-as.matrix(k0)
if(nrow(k0)>0){
  correct_each[k0,1]<-matrix(0,(nrow(k0)),1)
}
correct_sum<-sum(correct_each)
newp<-0.05/correct_sum
mannewp<-newp
manstandchoice<-1
no_porder<-which(no_p[,2]<=newp)
no_porder<-as.matrix(no_porder)
no_porderrow<-nrow(no_porder)
gg<-orderno

if(nrow(orderno)>1){
  for (ii in 1:(nrow(orderno)-1)){
    for (jj in (ii+1):(nrow(orderno))){
      ci<- chr_pos[orderno[ii],1]
      cj<- chr_pos[orderno[jj],1]
      if (ci==cj){
        ye<-abs(chr_pos[orderno[ii],2]-chr_pos[orderno[jj],2])
        if (ye<=((svrad)*1000)){
          gg[jj,1]<-0
        }
      }
    }
  }
}


parms.pchange<-parms
parmsp<-as.matrix(parms.pchange[,10])
locsub<-which(parmsp==0)
if(length(locsub)!=0){
  pmin<-min(parmsp[parmsp!=0])
  subvalue<-10^(1.1*log10(pmin))
  parms.pchange[locsub,10]<-subvalue
}else{
  parms.pchange<-parms
}

if(inputform==1){
  #output result1 using mrMLM numeric format
  parmsShow<-parms[,-1]
  meadd<-matrix(1,nrow(parms),1)
  meadd[which(parms[,10]<newp),1]<-sprintf("%.4e",newp)
  meadd[which(parms[,10]>=newp),1]<-"  "
  tempparms<-parms[,4:10]
  tempparms[,7]<--log10(tempparms[,7])
  tempparms[which(abs(tempparms)>=1e-4)]<-round(tempparms[which(abs(tempparms)>=1e-4)],4)
  tempparms[which(abs(tempparms)<1e-4)]<-as.numeric(sprintf("%.4e",tempparms[which(abs(tempparms)<1e-4)]))
  parmsShow<-cbind(genRaw[-1,1],parms[,2:3],tempparms,genRaw[-1,4],meadd)
  colnames(parmsShow)<-c("RS#","Chromosome","Marker position (bp)","Mean","Sigma2","Sigma2_k","SNP effect (mrMLM)","Sigma2_k_posteriori","Wald","'-log10(P) (mrMLM)'","Genotype for code 1","Significance")
}
if(inputform==2){
  #output result1 using mrMLM character format
  parmsShow<-parms[,-1]
  outATCG<-matrix(outATCG,,1)
  meadd<-matrix(1,nrow(parms),1)
  meadd[which(parms[,10]<newp),1]<-sprintf("%.4e",newp)
  meadd[which(parms[,10]>=newp),1]<-"  "
  tempparms<-parms[,4:10]
  tempparms[,7]<--log10(tempparms[,7])
  tempparms[which(abs(tempparms)>=1e-4)]<-round(tempparms[which(abs(tempparms)>=1e-4)],4)
  tempparms[which(abs(tempparms)<1e-4)]<-as.numeric(sprintf("%.4e",tempparms[which(abs(tempparms)<1e-4)]))
  parmsShow<-cbind(genRaw[-1,1],parms[,2:3],tempparms,outATCG,meadd)
  colnames(parmsShow)<-c("RS#","Chromosome","Marker position (bp)","Mean","Sigma2","Sigma2_k","SNP effect (mrMLM)","Sigma2_k_posteriori","Wald","'-log10(P) (mrMLM)'","Genotype for code 1","Significance")
}
if(inputform==3){
  #output result1 using TASSEL format
  parmsShow<-parms[,-1]
  outATCG<-matrix(outATCG,,1)
  #outATCG<-unlist(strsplit(outATCG,""))
  #outATCG<-matrix(outATCG[c(TRUE,FALSE)],,1)
  meadd<-matrix(1,nrow(parms),1)
  meadd[which(parms[,10]<newp),1]<-sprintf("%.4e",newp)
  meadd[which(parms[,10]>=newp),1]<-"  "
  tempparms<-parms[,4:10]
  tempparms[,7]<--log10(tempparms[,7])
  tempparms[which(abs(tempparms)>=1e-4)]<-round(tempparms[which(abs(tempparms)>=1e-4)],4)
  tempparms[which(abs(tempparms)<1e-4)]<-as.numeric(sprintf("%.4e",tempparms[which(abs(tempparms)<1e-4)]))
  parmsShow<-cbind(genRaw[-1,1],parms[,2:3],tempparms,outATCG,meadd)
  colnames(parmsShow)<-c("RS#","Chromosome","Marker position (bp)","Mean","Sigma2","Sigma2_k","SNP effect (mrMLM)","Sigma2_k_posteriori","Wald","'-log10(P) (mrMLM)'","Genotype for code 1","Significance")
}

rm(genRaw)
gc()


gg<-as.matrix(gg)
misfit<-numeric()
kk<- numeric()
kk0<- numeric()
l0<- numeric()
bong<-no_porderrow
if (bong>0){
  g0<-gg[1:no_porderrow,1]
  g0<-as.matrix(g0)
  kk0<-no_porderrow
  no_porderrow<-which(g0>0)
  no_porderrow<-as.matrix(no_porderrow)
  g0<-g0[no_porderrow,1]
  g0<-as.matrix(g0)
  xxx0<-genq[c(g0),]
  if(dim(g0)[1]==1){
    xxx0<-as.matrix(xxx0)
  }
  if(dim(g0)[1]>1)
  {
    xxx0<-as.matrix(xxx0)
    xxx0<-t(xxx0)
  }
  phe<-as.matrix(phe)
  if((flagps==1)||(exists("psmatrix")==FALSE))
  {
    par<-likelihood(matrix(1,(nrow(xxx0)),1),xxx0,phe,bbo=NULL)
    lod<-par
  }else if(flagps==0)
  {
    temp<-cbind(matrix(1,(nrow(xxx0)),1),psmatrix)
    par<-likelihood(temp,xxx0,phe,bbo=NULL)
    lod<-par
  }
  kk<-which(lod>=1.5)
  kk<-as.matrix(kk)
  kk1<-which(lod<1.5)
  kk1<-as.matrix(kk1)
  if ((nrow(kk1))>0){
    misfit<-g0[kk1,1]
    misfit<-as.matrix(misfit)
  }
  if ((nrow(kk))>0){
    g0<-as.matrix(g0)
    g0<-g0[kk,1]
    xx0<-xxx0[,kk]
    lo<-lod[kk,1]
  }
  if ((nrow(kk))==0){kk<-0}
}
if (bong==0){
  kk0<-0
  kk<-0
}
nleft<-as.matrix(gg[(kk0+1):(nrow(gg)),1])
if ((length(misfit))>0){gg<-rbind(nleft,misfit)}
if ((length(misfit))==0){gg<-nleft}
a1<-which(gg>0)
a1<-as.matrix(a1)
a2<-gg[a1,1]
a2<-as.matrix(a2)

if(nrow(a2)>1){
  xx<-t(genq[c(a2),])
}else{
  xx<-genq[c(a2),]  
}

xx<-as.matrix(xx)
if((flagps==1)||(exists("psmatrix")==FALSE))
{
  if (length(kk)>1){xin<-cbind(matrix(1,(nrow(xx)),1),xx0)}
  if (length(kk)==1){
    if(kk==0){
      xin<- matrix(1,(nrow(xx)),1)
    }
    if(kk>0){
      xin<-cbind(matrix(1,(nrow(xx)),1),xx0)
    }
  }
}else if(flagps==0)
{
  temp<-cbind(matrix(1,(nrow(xx)),1),psmatrix)
  if (length(kk)>1){xin<-cbind(temp,xx0)}
  if (length(kk)==1){
    if(kk==0){
      xin<-temp
    }
    if(kk>0){
      xin<-cbind(temp,xx0)
    }
  }
}
xin<-as.matrix(xin)
par1<-ebayes_EM(xin,xx,phe)
par<-par1$wang

w2<-which(par[,1]<=0.01)

if(length(w2)!=0){
  w2<-as.matrix(w2)
  ww<- numeric()
  if ((nrow(w2))>0){
    orderno<-a2[w2,1]
    orderno<-as.matrix(orderno)
    x3<-cbind(xin,xx[,w2])
    x3<-as.matrix(x3)
    lodfix<-matrix(x3[,1],nrow(x3),)
    lodrand<-matrix(x3[,2:(ncol(x3))],nrow(x3),)
    if((flagps==1)||(exists("psmatrix")==FALSE))
    {
      lod<-likelihood(lodfix,lodrand,phe,bbo=NULL)
    }else if(flagps==0)
    {
      temp<-cbind(psmatrix,lodfix)
      lod<-likelihood(temp,lodrand,phe,bbo=NULL)
    }
    w3<-which(lod[,1]>=(svmlod))
    w3<-as.matrix(w3)
    if ((kk[1])>0){
      g0<-as.matrix(g0)
      orderno<-rbind(g0,orderno)
      orderno<-as.matrix(orderno)
    }
    #if ((nrow(w3))==0){ww<-0}change20190125
    
    if ((nrow(w3)!=0)&&(w3[1]>0)){
      if((flagps==1)||(exists("psmatrix")==FALSE))
      {
        lo<-lod[w3,1]
        ww<-orderno[w3,]
      }else if(flagps==0)
      {
        lo<-lod[w3,1]
        no_loc<-w3-ncol(psmatrix)
        ww<-orderno[no_loc,]
      }
    }
    
  }
  if ((nrow(w2))==0){
    g0<-as.matrix(g0)
    lo<-as.matrix(lo)
    yang<-which(lo>=(svmlod))
    yang<-as.matrix(yang)
    if ((nrow(yang))>0){
      ww<-g0[yang,1]
      lo<-lo[yang,1]
    }
    #if ((nrow(yang))==0){ww<-0}
  }
  #ww<-as.matrix(ww)
  needww<-ww
  if (length(ww)>=1){
    #ww<-as.matrix(ww)
    if (length(ww)>1){
      
      ww<-as.matrix(ww)
      
      if((flagps==1)||(exists("psmatrix")==FALSE))
      {
        ex<-cbind(matrix(1,(nrow(xx)),1),t(genq[c(ww),]))
      }else if(flagps==0)
      {
        ex<-cbind(cbind(matrix(1,(nrow(xx)),1),psmatrix),t(genq[c(ww),]))
      }
      
    }else{
      if((flagps==1)||(exists("psmatrix")==FALSE))
      {
        ex<-cbind(matrix(1,(nrow(xx)),1),as.matrix(genq[c(ww),]))
      }else if(flagps==0)
      {
        ex<-cbind(cbind(matrix(1,(nrow(xx)),1),psmatrix),as.matrix(genq[c(ww),]))
      }  
    }
    rm(genq)
    gc()
    
    ex<-as.matrix(ex)
    cui<-det(t(ex)%*%ex)
    p1<-rep(1,ncol(ex))
    p2<-diag(p1)
    if (cui<1e-6){bbbb<-solve(t(ex)%*%ex+p2*0.01)%*%t(ex)%*%phe}
    if (cui>=1e-6){ bbbb<-solve(t(ex)%*%ex)%*%t(ex)%*%phe }
    if((flagps==1)||(exists("psmatrix")==FALSE))
    {
      eeff<-bbbb[2:(nrow(bbbb)),1]
    }else if(flagps==0)
    {
      eeff<-bbbb[(2+ncol(psmatrix)):(nrow(bbbb)),1]
    }
    
    eeff<-as.matrix(eeff)
    er<-as.numeric()
    her<-as.numeric()
    if((flagps==1)||(exists("psmatrix")==FALSE))
    {
      excol<-ncol(ex)
      for(i in 1:(excol-1))
      {
        em<-ex[,(1+i)]
        as1<-length(which(em==1))/nrow(ex)
        as2<-1-as1
        er<-rbind(er,(1-(as1-as2)*(as1-as2))*eeff[i]*eeff[i])
      }
      v0<-(1/(nrow(ex)-1))*(t(phe-ex%*%bbbb)%*%(phe-ex%*%bbbb))
      
      if(var(phe)>=(sum(er)+v0)){
        her<-(er/as.vector(var(phe)))*100 
      }else{
        her<-(er/as.numeric(sum(er)+v0))*100
      }
      
    }else if(flagps==0)
    {
      excol<-ncol(ex)
      for(i in 1:(excol-1-ncol(psmatrix)))
      {
        em<-ex[,(1+ncol(psmatrix)+i)]
        as1<-length(which(em==1))/nrow(ex)
        as2<-1-as1
        er<-rbind(er,(1-(as1-as2)*(as1-as2))*eeff[i]*eeff[i])
      }
      v0<-(1/(nrow(ex)-1))*(t(phe-ex%*%bbbb)%*%(phe-ex%*%bbbb))
      
      if(var(phe)>=(sum(er)+v0)){
        her<-(er/as.vector(var(phe)))*100 
      }else{
        her<-(er/as.numeric(sum(er)+v0))*100
      }
    }
    
    vee<-round(v0,4)
    pee<-round(var(y),4)
    
    if(nrow(her)>1){
      vees<-matrix("",nrow = nrow(her),1)
      pees<-matrix("",nrow = nrow(her),1)
      pees[1,1]<-pee
      vees[1,1]<-vee
    }else{
      pees<-as.matrix(pee)
      vees<-as.matrix(vee)
    }
    
    x<-deepcopy(gen,,3:nrow(gen))
    xxxx<-as.matrix(x[,ww])
    
    rm(x)
    gc()
    
    xxmaf<-t(xxxx)
    
    maf.fun<-function(snp){
      leng<-length(snp)
      snp1<-length(which(snp==1))
      snp11<-length(which(snp==-1))
      snp0<-length(which(snp==0))
      ma1<-(2*snp1+snp0)/(2*leng)
      ma2<-(2*snp11+snp0)/(2*leng)
      maf<-min(ma1,ma2)
      return(maf)
    }
    
    maf<-apply(xxmaf,1,maf.fun)
    maf<-as.matrix(round(maf,4))
    
    eeff[which(abs(eeff)>=1e-4)] <- round(eeff[which(abs(eeff)>=1e-4)],4)
    eeff[which(abs(eeff)<1e-4)] <- as.numeric(sprintf("%.4e",eeff[which(abs(eeff)<1e-4)]))
    lo[which(abs(lo)>=1e-4)] <- round(lo[which(abs(lo)>=1e-4)],4)
    lo[which(abs(lo)<1e-4)] <- as.numeric(sprintf("%.4e",lo[which(abs(lo)<1e-4)]))
    her[which(abs(her)>=1e-4)] <- round(her[which(abs(her)>=1e-4)],4)
    her[which(abs(her)<1e-4)] <- as.numeric(sprintf("%.4e",her[which(abs(her)<1e-4)]))
    log10P <- as.matrix(-log10(pchisq(lo*4.605,1,lower.tail = F)))
    
    log10P[which(abs(log10P)>=1e-4)] <- round(log10P[which(abs(log10P)>=1e-4)],4)
    log10P[which(abs(log10P)<1e-4)] <- as.numeric(sprintf("%.4e",her[which(abs(log10P)<1e-4)]))

    if (length(ww)>1){
      wan<-data.frame(parmsShow[needww,1],chr_pos[ww,],eeff,lo,log10P,her,maf,parmsShow[needww,11])
      wan<-wan[order(wan[,2]),]
      wan<-data.frame(wan,vees,pees)
    }else{
      
      wan<-data.frame(parmsShow[needww,1],t(as.matrix(chr_pos[ww,])),eeff,lo,log10P,her,maf,parmsShow[needww,11],vees,pees)  
    }
    colnames(wan)<-c("RS#","Chromosome","Marker position (bp)","QTN effect","LOD score","'-log10(P)'","r2 (%)","MAF","Genotype for code 1","Var_error","Var_phen (total)")
  }
}
if(is.null(parmsShow)==FALSE){
  parmsShow<-parmsShow[,-c(4,5,6,8,9,12)]
}
output<-list(result1=parmsShow,result2=wan)
return(output) 
}
}