R/coexpansion_pulses.R

In gehara/PipeMaster: Building and Simulating Coalescent models.

sim.coexp.pulses<-function(nsims,
                    max.pulses,
                    coexp.prior,
                    buffer,
                    Ne.prior,
                    NeA.prior,
                    time.prior,
                    gene.prior,
                    alpha=F,
                    append.sims=F,
                    path=getwd())
{

  setwd(path)


  if(append.sims==F){
    simulations<-matrix(nrow=1,ncol=20)
    simulations[1,]<-c("pulse","ts","E(t)","DI",
                       "var.pi","mean.pi","skew.pi","kur.pi",
                       "var.ss","mean.ss","skew.ss","kur.ss",
                       "var.H","mean.H","skew.H","kur.H",
                       "var.TD","mean.TD","skew.TD","kur.TD")

    write.table(simulations,file="simulations.txt", quote=F,row.names=F, col.names=F, sep="\t")

    #populations.par<-matrix(nrow=1,ncol=nrow(NeA.prior)*4)
    #pop.names<-NULL
    #for(i in 1:nrow(NeA.prior)){
    #pop.names<-cbind(pop.names,t(c(paste("Ne",i,sep=""),paste("Exp.time",i,sep=""),paste("NeA",i,sep=""),paste("mi",i,sep=""))))
    #}
    #populations.par[1,]<-pop.names
    #write.table(populations.par,file="pop_parameters.txt", quote=F,row.names=F, col.names=F, sep="\t")
  }


  TIME<-system.time(for (i in 1:nsims){

    x<-coexp.sample.pars.pulses(nruns=1,coexp.prior=coexp.prior,max.pulses=max.pulses,buffer=buffer,Ne.prior=Ne.prior,
                         NeA.prior=NeA.prior,time.prior=time.prior,gene.prior=gene.prior)

    y<-coexp.MS(MS.par=x$MS.par, gene.prior = gene.prior,alpha=alpha)

    z<-coexp.sumstat(ms.output=y,gene.prior=gene.prior)

    simulations<-c(x$coexp.par,z)

    #populations.par<-unlist(x$pop.par)

    write.table(t(simulations),file="simulations.txt", quote=F,row.names=F, col.names=F, append=T, sep="\t")
    #write.table(t(populations.par),file="pop_parameters.txt", quote=F,row.names=F, col.names=F, append=T,sep="\t")
    print(paste(i,"sims of",nsims,"| pulses = ",x$coexp.par[,1]))
   })
  print(TIME)
}



coexp.sample.pars.pulses<-function(nruns,
                                   max.pulses,
                                   buffer,
                                   Ne.prior,
                                   coexp.prior,
                                   NeA.prior,
                                   time.prior,
                                   gene.prior){

  dmode <- function(x) {
    den <- density(x, kernel=c("gaussian"))
    (den$x[den$y==max(den$y)])
  }

  MS.par<-list(NULL)
  pop.par<-list(NULL)
  coexp.par<-matrix(nrow=nruns,ncol=4)
  nspecies<-nrow(Ne.prior)

  for(i in 1:nspecies){
    mat<-matrix(nrow=nruns,ncol=4)
    MS.par[[i]]<-mat
    pop.par[[i]]<-mat
  }
  for(j in 1:nruns){
    time.prior.B<-time.prior

    max.pulse.space<-coexp.prior[2]/buffer

    range<-coexp.prior[2]-coexp.prior[1]
    x<-range/max.pulse.space
    priors<-(x*(1:max.pulse.space))+coexp.prior[1]
    priors<-c(coexp.prior[1],priors)

    e.t<-vector()
    for(i in 1:(length(priors)-1)){
      e.t[i]<-runif(1,priors[i],priors[i+1])
    }

    pulses<-sample(1:max.pulses,1)

    pulse.times<-sort(sample(e.t,pulses))


    time.prior.B[,c(3,4)]<-replicate(nrow(time.prior.B),sample(pulse.times,1))


    Et<-mean(time.prior.B[,3])
    Disp.index<-var(time.prior.B[,3])/Et
    Ts<-dmode(time.prior.B[,3])
    coexp.par[j,]<-c(pulses,Ts,Et,Disp.index)

    for(i in 1:nspecies){
      ms.par<-NULL

      Ne <- runif(1, Ne.prior[i,3], Ne.prior[i,4])
      Ne.EXP.t <- time.prior.B[i,3]/time.prior[i,5] #corrects by generations
      theta.A.ratio <- runif(1, NeA.prior[i,3], NeA.prior[i,4])# thetaA (NeA) ratio
      NeA <- Ne*theta.A.ratio
      mi <- do.call(as.character(gene.prior[i,2]),args=list(1,gene.prior[i,3],gene.prior[i,4]),quote=F)
      while(mi<0){
        mi <- do.call(as.character(gene.prior[i,2]),args=list(1,gene.prior[i,3],gene.prior[i,4]),quote=F)
      }
      Ne <- Ne*gene.prior[i,7] # Ne times inheritance scalar: cerrects the Ne
      theta=4*Ne*mi*gene.prior[i,5] # 4N x mutation per pb x bp
      scalar=4*Ne # generates the coalescent scalar
      EXP.time=Ne.EXP.t/scalar # expansion time / 4N

      g.rate=-log(NeA/Ne)/Ne.EXP.t

      ms.par<-cbind(theta,EXP.time,theta.A.ratio,g.rate)
      po.par<-c(Ne,time.prior.B[i,3],NeA,mi)
      MS.par[[i]][j,]<-ms.par
      pop.par[[i]][j,]<-po.par
    }
    #print(j)
  }
  #write.table(coexp.par,file="sim.par.txt", quote=F,row.names=F, col.names=F, append=T, sep="\t")
  #return(MS.par)
  pars<-list(NULL,NULL,NULL)
  names(pars)<-c("coexp.par","MS.par","pop.par")
  pars$coexp.par<-coexp.par
  pars$MS.par<-MS.par
  pars$pop.par<-pop.par
  return(pars)
}