R/DoCluster.R

In mssm-msf-2019/BiostatsALL:

#' Save output of a heatmap built from a decision matrix and coefficients from limma model
#' @description a function that preprocess output from limma model and draws a heatmap according to a set of parameters
#' @param Decision is a matrix indicating up(1), down(-1) regulation for each contrast is a gene list.
#' @param ebfit is a matrix of coefficients for each contrast
#' @param reset is the expression set used as input for the limma model
#' @param dmeth is the method for distance
#' @param hmeth is the agglomerative method used for the hierarchical clustering
#' @param cols is a vector defining how the columns in the hierarchical heatmap should be ordered
#' @param Group is a vector indicating the levels associated with columns in the expression sets
#' @param Patients is a vector indicating the patients IDs associated with columns in the expression sets
#' @examples 
#' DoCluster(Decision = D, ebfit = fit, reset = eset, dmeth = "euclidean" , hmeth = "complete" , cols =NULL,Group=Group, Patients = IDs)


DoCluster<-function(Decision,ebfit,reset,dmeth="euclidean",hmeth="complete",cols=NULL){
  somediff<-(rowSums(Decision!=0)>0)
  
  symb<-unlist(mget(featureNames(reset),hgu133a2SYMBOL))
  somediff[is.na(symb)]<-FALSE
  
  mat<-exprs(reset)[somediff,]
  symb<-unlist(mget(featureNames(reset)[somediff],hgu133a2SYMBOL))
  name<-unlist(mget(featureNames(reset)[somediff],hgu133a2GENENAME))
  
  g<-pData(reset)$Group
  
  mat<-mat[,order(g)]
  cn<-(pData(reset)$Patient)[order(g)]
  g<-g[order(g)]
  DoCluster<-function(Decision,ebfit,reset,dmeth="euclidean",hmeth="complete",cols=NULL){
    somediff<-(rowSums(Decision!=0)>0)
    
    symb<-unlist(mget(featureNames(reset),hgu133a2SYMBOL))
    somediff[is.na(symb)]<-FALSE
    
    mat<-exprs(reset)[somediff,]
    symb<-unlist(mget(featureNames(reset)[somediff],hgu133a2SYMBOL))
    name<-unlist(mget(featureNames(reset)[somediff],hgu133a2GENENAME))
    
    g<-pData(reset)$Group
    
    mat<-mat[,order(g)]
    cn<-(pData(reset)$Patient)[order(g)]
    g<-g[order(g)]
    
    AveExp<-ebfit$Amean[somediff]
    o<-order(AveExp, decreasing=TRUE)
    rc<-heat.colors(nrow(mat))[o][o]
    
    desc<-paste(symb,name,sep=" - ")
    cc<-getgray(g)
    
    
    ho<-heatmap.2_MSF(mat, distfun=function(c){Dist(c,method=dmeth)},
                      hclustfun=function(c){hclust(c,method=hmeth)},
                      Colv=cols, col=greenred.colors(50),labRow=symb, labCol=cn, 
                      RowSideColors=rc,ColSideColors=cc,cexRow=0.4,cexCol=1,
                      trace='none', density.info='none', keysize=0.8, scale='row')
  }
  
  AveExp<-ebfit$Amean[somediff]
  o<-order(AveExp, decreasing=TRUE)
  rc<-heat.colors(nrow(mat))[o][o]
  
  desc<-paste(symb,name,sep=" - ")
  cc<-getgray(g)
  
  
  ho<-heatmap.2_MSF(mat, distfun=function(c){Dist(c,method=dmeth)},
                    hclustfun=function(c){hclust(c,method=hmeth)},
                    Colv=cols, col=greenred.colors(50),labRow=symb, 
                    labCol=cn, RowSideColors=rc,
                    ColSideColors=cc,
                    cexRow=0.4,cexCol=1,trace='none', density.info='none', keysize=0.8, scale='row')
}