R/MultipleClassGSEA.R

Defines functions MCGOContents ExtractStats PlotMultipleEnrichmentPlots QuickGSEA ExtractMCGO RunGSEA MCGOpdf PlotMultipleClassGSEAObject MultipleClassGSEA

###GSEA on Unaffected Genes####
MultipleClassGSEA<-function(data.GSEA, Comparison1, Comparison2, GMTList, classvec=NULL, runGSEAcode=TRUE, reshuffling.type, directory=getwd(), uniquelabel="", abbrev_comp=FALSE){
  #   os<-Sys.info()['sysname']
  #   if(os=="Darwin"){GSEA.program.location <- "/Library/Frameworks/R.framework/Resources/library/GSEA/GSEA.1.0.R"}   #  R source program (change pathname to the rigth location in local machine)
  #   source(GSEA.program.location, verbose=T, max.deparse.length=9999)
  datestamp<-format(Sys.Date(), format="%Y%m%d")
  if(uniquelabel==""){
    uniquelabel<-datestamp
  }
  mdirectory<-file.path(directory)
  rdirectory<-file.path(mdirectory, uniquelabel)
  fdirectory<-file.path(rdirectory, paste("Files-", datestamp, sep=""))
  odirectory<-file.path(rdirectory, paste("Output-", datestamp, sep=""))

  GMTfile<-file.path(fdirectory, "GMTFile.gmt")
  Comp1<-Comparison1
  Comp2<-Comparison2
  if(length(Comp1)==1){Comp1<-rep(Comparison1, length(Comparison2))}
  if(length(Comp2)==1){Comp2<-rep(Comparison2, length(Comparison1))}
  if(abbrev_comp==TRUE) {
        prefix<-paste(stringr::str_replace_all(stringr::str_replace_all(Comparison1, c("[[:lower:]]"), ""), "([.])", ""),
        stringr::str_replace_all(stringr::str_replace_all(Comparison2, c("[[:lower:]]"), ""), "([.])", ""), sep="v")
        }else{
          prefix<-paste(Comparison1, Comparison2, sep="_vs_")
        }
  if(length(Comparison2)!=1 && length(Comparison1)!=1){stop("Input Problem")}
  GSEAcomplist<-list(Number=max(c(length(Comparison1), length(Comparison2))), Comp1=Comp1, Comp2=Comp2,
                     Prefix=prefix,
                     Signreverse=!substring(Comparison1,1,1)<substring(Comparison2,1,1))
  Objectinfo<-list(GSEACompList=GSEAcomplist, GMTList=GMTList, Directory=odirectory, TimeStamp=Sys.time())
  MCGO<-new("MultipleClassGSEAObject", ObjectInfo=Objectinfo,
            Data=list(length=GSEAcomplist[["Number"]]),
            PlotData=list(length=GSEAcomplist[["Number"]]))
  MCGO@Data<-rep(list(list()), length(GMTList))
  MCGO@PlotData<-rep(list(data.frame(max=numeric(0), min=numeric(0), lRES=numeric(0), uRES=numeric(0), dotted=numeric(0))), length(GMTList))
  names(MCGO@PlotData)<-names(GMTList)
  statsOut.df<-data.frame()
  stats.df<-list()
  if(runGSEAcode==TRUE){
    #     os<-Sys.info()['sysname']
    #     if(os=="Darwin"){GSEA.program.location <- "/Library/Frameworks/R.framework/Resources/library/GSEA/GSEA.1.0.R"}   #  R source program (change pathname to the rigth location in local machine)
    #     source(GSEA.program.location, verbose=T, max.deparse.length=9999)
    dir.create(rdirectory, showWarnings=FALSE)
    dir.create(fdirectory, showWarnings=FALSE)
    dir.create(odirectory, showWarnings=FALSE)
    gsea.write.gmt(GMTList, GMTfile)
  }
  for(i in 1:GSEAcomplist[["Number"]]){
    file.cls<-file.path(fdirectory, paste(GSEAcomplist$Prefix[i], ".cls", sep=""))
    data.cls<-as.character(classvec[classvec %in% c(GSEAcomplist$Comp1[i],GSEAcomplist$Comp2[i])])
    file.gct<-file.path(fdirectory, paste(GSEAcomplist$Prefix[i], ".gct", sep=""))
    col.sel<-classvec %in% c(GSEAcomplist$Comp1[i],GSEAcomplist$Comp2[i])
    data.gct<-data.GSEA[,col.sel]
    wdirectory<-paste(odirectory, GSEAcomplist$Prefix[i], "/",sep="")
    if(runGSEAcode==TRUE){
      gsea.write.cls(data.cls, file.cls)
      gsea.write.gct(data.gct, file.gct)
      dir.create(wdirectory, showWarnings = FALSE)
      RunGSEA(in.data = file.path(fdirectory, paste(GSEAcomplist$Prefix[i], ".gct", sep="")),
              in.cls =file.path(fdirectory, paste(GSEAcomplist$Prefix[i], ".cls", sep="")),
              in.gmt =  GMTfile,
              directory      = wdirectory,
              prefix            = GSEAcomplist$Prefix[i],
              reshuffling.type      = reshuffling.type,
              signreverse          = GSEAcomplist$Signreverse[i])
    }
    for(j in 1:length(GMTList)){
      ###CREATE DF of MCGO DATA
      regex<-paste("^",GSEAcomplist$Prefix[i], ".", names(GMTList)[j], ".report.",sep="")
      filename<-grep(regex, list.files(wdirectory), value=TRUE)
      #browser()
      if(length(filename)==0){df<-data.frame(File="notfound", regex=regex, GMTEntry = names(GMTList)[j])}else{
        Rep<-read.delim(paste(wdirectory, filename, sep=""), header=TRUE, stringsAsFactors=FALSE)
        df<-data.frame()
        #yrug<--(.2+(.1*(i-1)))
        df<-cbind.data.frame(as.numeric(Rep$RES), as.numeric(Rep$LIST.LOC), as.character(Rep$CORE_ENRICHMENT), as.character(Rep$GENE))
        colnames(df)<-c("RES", "LOC", "ENRICHMENT", "GENE")
        MCGO@Data[[j]][[i]]<-df
        names(MCGO@Data[[j]])[i]<-GSEAcomplist$Prefix[i]
        ###CREATE DF of MCGO PLOTDATA
        max=df$LOC[which(df$RES == max(df$RES))][1]
        min=df$LOC[which(df$RES == min(df$RES))][1]
        lRES<-df$RES[which(df$RES == min(df$RES))][1]
        uRES<-df$RES[which(df$RES == max(df$RES))][1]
        if(abs(lRES)>(abs(uRES))){dotted<-min} else {dotted<-max}
        MCGO@PlotData[[j]][i,]<-c(max,min,lRES,uRES, dotted)
      }
      #ystats<-vector()
      #         for(i in 1:length(filelist)){
      #           df<-dflist[[i]]
      #           df$yrug<-min(lRES)-(.2+(.1*(i-1)))
      #           dflist[[i]]<-df
      #         }
    }
    names(MCGO@Data)<-names(GMTList)
    regex<-paste("^",GSEAcomplist$Prefix[i], ".SUMMARY.RESULTS.REPORT",sep="")
    filename<-grep(regex, list.files(wdirectory), value=TRUE)
    if(length(filename)>1){
      tmp<-read.delim(paste(wdirectory, filename[1], sep=""), header=TRUE, stringsAsFactors=FALSE)
      for(j in 2:length(filename)){
        tmp2<-read.delim(paste(wdirectory, filename[j], sep=""), header=TRUE, stringsAsFactors=FALSE)
        tmp<-rbind(tmp, tmp2[1:nrow(tmp2),])
      }
      stats.df[[i]]<-tmp
    }
    else
    {
      stats.df[[i]]<-read.delim(paste(wdirectory, filename, sep=""), header=TRUE, stringsAsFactors=FALSE)
    }
    #     for(j in 1:length(GMTList)){
    #       statsOut.df[i,j]<-stats.df$FDR.q.val[j]
    #     }
    #     for(j in 1:length(GMTList)){
    #       statsOut.df[i,j]<-stats.df[[i]]$FDR.q.val[j]
    #     }
  }
  MCGO@Stats<-stats.df
  names(MCGO@Stats)<-GSEAcomplist$Prefix
  print(MCGO@ObjectInfo$GSEACompList)
  print(names(MCGO@ObjectInfo[[2]]))
  print(MCGO@ObjectInfo$Directory)
  print(MCGO@ObjectInfo$TimeStamp)
  return(MCGO)
}

PlotMultipleClassGSEAObject<-function(MCGO, index, plotcols=rep("Black", length(MCGO@Data[[index]]))){
  dflist<-MCGO@Data[[index]]
  plotdf<-MCGO@PlotData[[index]]
  #statindex<-match(names([email protected][[2]])[index], names([email protected][[2]])[order(names([email protected][[2]]))])
  fdr<-vector()
  for(i in 1:length(MCGO@Data[[index]])){
    statindex<-match(names(MCGO@ObjectInfo[[2]])[index], MCGO@Stats[[i]]$GS)
    fdr[i]<-round(MCGO@Stats[[i]]$FDR.q.val[statindex], 3)
  }
  #fdrstats<-data.frame(FDR=fdr, lRES=rep(min(MCGO[email protected][[index]]$lRES)-0.2, length([email protected][[index]])))
  x<-vector()
  y<-vector()
  lRES<-vector()
  lRES=rep(min(MCGO@PlotData[[index]]$lRES), length(MCGO@Data[[index]]))
  for(i in 1:length(fdr)){
    x[i]<--300
    y[i]<-lRES[i]-((i-1)*.1)
  }
  for(i in 1:length(MCGO@Data[[index]])){
    YRUG<-rep(y[i], nrow(dflist[[i]]))
    dflist[[i]]<-cbind(dflist[[i]], YRUG, stringsAsFactors=FALSE)
  }
  fdrstats<-data.frame(FDR=fdr, lRES=lRES, x=x, y=y)
  g<-ggplot2::ggplot() +
    ggplot2::geom_line(data=dflist[[1]], ggplot2::aes(x=LOC, y=RES), colour=plotcols[1])+
    ggplot2::geom_vline(data=plotdf[1,], ggplot2::aes(xintercept=dotted), colour=plotcols[1], linetype="dotted", size=0.8)+
    ggplot2::geom_abline(intercept=0, slope=0)+
    ggplot2::geom_point(data=dflist[[1]],ggplot2::aes(x=LOC, y=YRUG, size=as.factor(ENRICHMENT)),colour=plotcols[1], shape=124)+
    #geom_text(data=stats, colour=plotcols[1], ggplot2::aes(label = fdrstats[1], x = -200, y = -0.2))+
    ggplot2::theme_bw()
  if(length(dflist)>1){
    for(i in 2:length(dflist)){
      g<-g+ggplot2::geom_line(data=dflist[[i]], ggplot2::aes(x=LOC, y=RES), colour=plotcols[i])
      g<-g+ggplot2::geom_vline(data=plotdf[i,], ggplot2::aes(xintercept=dotted), colour=plotcols[i], linetype="dotted", size=0.8)
      g<-g+ggplot2::geom_point(data=dflist[[i]],ggplot2::aes(x=LOC, y=YRUG, size=as.factor(ENRICHMENT)),colour=plotcols[i], shape=124)
      g<-g+ ggplot2::scale_size_manual(values = c(3,6))
      #g<-g+ scale_size_discrete(guide=FALSE)
      g<-g+ ggplot2::theme(legend.position="none")
    }
  }
  g<-g+ ggplot2::labs(title=names(MCGO@Data)[index])
  #g <-g + geom_text(data=fdrstats, ggplot2::aes(label=FDR, x = rep(-200, nrow(fdrstats)), y = seq(min(lRES), (min(lRES)-(nrow(fdrstats)-1)*0.1), -0.1)), colour=plotcols, parse=FALSE, size=4)
  g <-g + ggplot2::geom_text(data=fdrstats, ggplot2::aes(label=FDR, x=x, y=y), colour=plotcols, parse=FALSE, size=4)
  print(g)
  return(g)
}

MCGOpdf<-function(MCGO, filename="", plotcols=rep("black", length(names(MCGO@ObjectInfo$GMTList))), gcolor=gcolor){
  pdf(filename, height=8.5, width=11)
  pie(rep(1,length(gcolor)), col=gcolor, labels=names(gcolor))
  for(i in 1:length(names(MCGO@ObjectInfo$GMTList))){
    PlotMultipleClassGSEAObject(MCGO,i, plotcols=plotcols)
  }
  dev.off()
}

RunGSEA<-function(in.data, in.cls, in.gmt, directory, prefix, signreverse, reshuffling.type){
  # GSEA 1.0 -- Gene Set Enrichment Analysis / Broad Institute
  # R script to run GSEA
  ######command###########
  GSEA( # Input/Output Files :-------------------------------------------
        input.ds =  in.data,                 # Input gene expression Affy dataset file in RES or GCT format
        input.cls = in.cls,                 # Input class vector (phenotype) file in CLS format
        gs.db =     in.gmt,          # Gene set database in GMT format
        output.directory      = directory,              # Directory where to store output and results (default: "")
        #  Program parameters :-------------------------------------------------------------------------------------------------------------------------
        doc.string            = prefix,        # Documentation string used as a prefix to name result files (default: "GSEA.analysis")
        non.interactive.run   = F,               # Run in interactive (i.e. R GUI) or batch (R command line) mode (default: F)
        reshuffling.type      = reshuffling.type, # Type of permutation reshuffling: "sample.labels" or "gene.labels" (default: "sample.labels"
        nperm                 = 1000,            # Number of random permutations (default: 1000)
        weighted.score.type   =  1,              # Enrichment correlation-based weighting: 0=no weight (KS), 1= weigthed, 2 = over-weigthed (default: 1)
        nom.p.val.threshold   = -1,              # Significance threshold for nominal p-vals for gene sets (default: -1, no thres)
        fwer.p.val.threshold  = -1,              # Significance threshold for FWER p-vals for gene sets (default: -1, no thres)
        fdr.q.val.threshold   = 1,            # Significance threshold for FDR q-vals for gene sets (default: 0.25)
        topgs                 = 20,              # Besides those passing test, number of top scoring gene sets used for detailed reports (default: 10)
        adjust.FDR.q.val      = F,               # Adjust the FDR q-vals (default: F)
        gs.size.threshold.min = 5,              # Minimum size (in genes) for database gene sets to be considered (default: 25)
        gs.size.threshold.max = 1500,             # Maximum size (in genes) for database gene sets to be considered (default: 500)
        reverse.sign          = signreverse,      # Reverse direction of gene list (pos. enrichment becomes negative, etc.) (default: F)
        preproc.type          = 0,               # Preproc.normalization: 0=none, 1=col(z-score)., 2=col(rank) and row(z-score)., 3=col(rank). (def: 0)
        random.seed           = 760435,          # Random number generator seed. (default: 123456)
        perm.type             = 0,               # For experts only. Permutation type: 0 = unbalanced, 1 = balanced (default: 0)
        fraction              = 1.0,             # For experts only. Subsampling fraction. Set to 1.0 (no resampling) (default: 1.0)
        replace               = F,               # For experts only, Resampling mode (replacement or not replacement) (default: F)
        save.intermediate.results = F,           # For experts only, save intermediate results (e.g. matrix of random perm. scores) (default: F)
        OLD.GSEA              = F,               # Use original (old) version of GSEA (default: F)
        use.fast.enrichment.routine = T          # Use faster routine to compute enrichment for random permutations (default: T)
  )

}

ExtractMCGO<-function(MCGO, name){
  if(length(which(names(MCGO@ObjectInfo$GMTList) %in% name))==0){
    stop("Data Not Found")
  }
  else
    index<-which(names(MCGO@ObjectInfo$GMTList) %in% name)
  dflist<-MCGO@Data[[index]]
  return(dflist)
}

QuickGSEA<-function(data.GSEA, Comp1, Comp2, classvec, GMT, directory, prefix, signreverse=FALSE, reshuffling.type="gene.labels"){
  file.cls<-paste(directory, "/", format(Sys.time(), "%a-%b-%d-%Y-%X"),  ".cls", sep="")
  data.cls<-as.character(classvec[classvec %in% c(Comp1, Comp2)])
  file.gct<-paste(directory, "/", format(Sys.time(), "%a-%b-%d-%Y-%X"),  ".gct", sep="")
  col.sel<-classvec %in% c(Comp1, Comp2)
  GMTfile<-paste(directory, "/", format(Sys.time(), "%a-%b-%d-%Y-%X"),  ".gmt", sep="")
  data.gct<-data.GSEA[,col.sel]
  odirectory<-paste(directory, "/Output", format(Sys.time(), "%a-%b-%d-%Y-%X"), "/", sep="")
  dir.create(odirectory, showWarnings=FALSE)
  gsea.write.gmt(GMT, GMTfile)
  gsea.write.cls(data.cls, file.cls)
  gsea.write.gct(data.gct, file.gct)
  RunGSEA(file.gct, file.cls, GMTfile, odirectory, prefix=format(Sys.time(), "%a-%b-%d-%Y-%X"), signreverse, reshuffling.type)
}

#debug(PlotMultipleEnrichmentPlots)
PlotMultipleEnrichmentPlots<-function(filelist, type=NULL, comp=NULL, geneset=NULL, plotcols=rep("Black", length(filelist)), stats=FALSE){
  dflist<-list()
  if(!any(c("files", "object") %in% type)){
    stop("You must select a valid type, options are 'files', or 'object'")
  }
  PlotData<-data.frame(max=numeric(0), min=numeric(0), lRES=numeric(0), uRES=numeric(0), dotted=numeric(0))
  if(type=="files"){
  for(i in 1:length(filelist)){
    dflist[[i]]<-read.delim(filelist[[i]], header=TRUE)
    max=dflist[[i]]$LIST.LOC[which(dflist[[i]]$RES == max(dflist[[i]]$RES))]
    min=dflist[[i]]$LIST.LOC[which(dflist[[i]]$RES == min(dflist[[i]]$RES))]
    lRES<-dflist[[i]]$RES[which(dflist[[i]]$RES == min(dflist[[i]]$RES))]
    uRES<-dflist[[i]]$RES[which(dflist[[i]]$RES == max(dflist[[i]]$RES))]
    if(abs(lRES)>(abs(uRES))){
      dotted<-dflist[[i]]$LIST.LOC[min(which(dflist[[i]]$CORE_ENRICHMENT=="YES"))]}
    else {
      dotted<-dflist[[i]]$LIST.LOC[max(which(dflist[[i]]$CORE_ENRICHMENT=="YES"))]}
    PlotData[i,]<-rbind(c(max,min,lRES,uRES, dotted), PlotData)
  }
  }
  if(type=="object"){
    newlist<-list()
    if(is.null(comp)){stop("an comp index must be selected for object plotting")}
    if(is.null(geneset)){stop("a geneset index must be selected for object plotting")}
    if(comp>1 && length(geneset) >1){stop("can only plot multiple genesets OR comparisons")}
    if(length(geneset)>1)
      {
        for(i in 1:length(geneset)){
        newlist[[i]]<-filelist[[geneset[i]]][[comp]]
        names(newlist)[i]<-paste(names(filelist)[geneset[i]], names(filelist[[geneset[i]]])[comp])
        }
    }
    if(length(geneset)==1 && length(comp)==1)
    {
      newlist<-list(filelist[[geneset]][[comp]])
      names(newlist)<-paste(names(filelist)[geneset], names(filelist[[geneset]])[comp])
    }
    if(length(comp)>1)
    {
      for(i in 1:length(comp)){
        newlist[[i]]<-filelist[[geneset]][[comp[i]]]
        names(newlist)[i]<-paste(names(filelist)[geneset], names(filelist[[geneset]])[comp[i]])
      }
    }
    for(i in 1:length(newlist)){
      dflist[[i]]<-newlist[[i]]
      colnames(dflist[[i]])<-c("RES","LIST.LOC","CORE_ENRICHMENT","GENE")
      max=dflist[[i]]$LIST.LOC[which(dflist[[i]]$RES == max(dflist[[i]]$RES))][1]
      min=dflist[[i]]$LIST.LOC[which(dflist[[i]]$RES == min(dflist[[i]]$RES))][1]
      lRES<-dflist[[i]]$RES[which(dflist[[i]]$RES == min(dflist[[i]]$RES))][1]
      uRES<-dflist[[i]]$RES[which(dflist[[i]]$RES == max(dflist[[i]]$RES))][1]
      if(abs(lRES)>(abs(uRES))){
        dotted<-dflist[[i]]$LIST.LOC[max(which(dflist[[i]]$CORE_ENRICHMENT=="YES"))]}
      else {
        dotted<-dflist[[i]]$LIST.LOC[max(which(dflist[[i]]$CORE_ENRICHMENT=="YES"))]}
      PlotData[i,]<-rbind(c(max,min,lRES,uRES, dotted), PlotData)
    }
  }
  x<-vector()
  y<-vector()
  lRES.global<-vector()
  lRES.global=rep(min(PlotData$lRES), length(dflist))
  for(i in 1:length(dflist)){
    x[i]<--300
    y[i]<-lRES.global[i]-((i-1)*.1)
  }
  for(i in 1:length(dflist)){
    YRUG<-rep(y[i], nrow(dflist[[i]]))
    dflist[[i]]<-cbind(dflist[[i]], YRUG, stringsAsFactors=FALSE)
  }
  if(length(plotcols)!=length(newlist)){stop("Color Input Insufficient")}
  plottitle<-vector()
  for(i in 1:length(newlist)){
    plottitle<-c(plottitle, paste(names(newlist)[i], plotcols[i], sep="-"))
  }
  plottitle<-paste(plottitle, collapse="\n")
  g<-ggplot2::ggplot() +
    ggplot2::geom_line(data=dflist[[1]], ggplot2::aes(x=LIST.LOC, y=RES), colour=plotcols[1])+
    ggplot2::geom_vline(data=PlotData[1,], ggplot2::aes(xintercept=dotted), colour=plotcols[1], linetype="dotted", size=0.8)+
    ggplot2::geom_abline(intercept=0, slope=0)+
    ggplot2::geom_point(data=dflist[[1]], ggplot2::aes(x=LIST.LOC, y=YRUG, size=as.factor(CORE_ENRICHMENT)),colour=plotcols[1], shape=124)+
    #geom_text(data=stats, colour=plotcols[1], ggplot2::aes(label = fdrstats[1], x = -200, y = -0.2))+
    ggplot2::theme_bw()+
    ggplot2::theme(legend.position="none")
  if(length(dflist)>1){
    for(i in 2:length(dflist)){
      g<-g+ggplot2::geom_line(data=dflist[[i]], ggplot2::aes(x=LIST.LOC, y=RES), colour=plotcols[i])
      g<-g+ggplot2::geom_vline(data=PlotData[i,], ggplot2::aes(xintercept=dotted), colour=plotcols[i], linetype="dotted", size=0.8)
      g<-g+ggplot2::geom_point(data=dflist[[i]], ggplot2::aes(x=LIST.LOC, y=YRUG, size=as.factor(CORE_ENRICHMENT)),colour=plotcols[i], shape=124)
      g<-g+ ggplot2::scale_size_manual(values = c(3,6))
      #g<-g+ scale_size_discrete(guide=FALSE)
      g<-g+ ggplot2::theme(legend.position="none")
    }
  }
  g<-g+ ggplot2::labs(title=plottitle)
  #print(g)
  return(g)
}


ExtractStats<-function(MCGO, index){
  return(MCGO@Stats[[index]][,c(1,2,5,6,7)])
}

MCGOContents<-function(MCGO){
  if(class(MCGO)!="MultipleClassGSEAObject"){stop("Input is not MCGO")}
  out<-list(Genesets=names(MCGO@Data), Comparisons=names(MCGO@Data[[1]]))
  return(out)
}


#
#
#
# EnrichmentPlot<- function (df, size = 1, line = FALSE, rug=TRUE, dotcolor = "white", highlight_le = TRUE, fillcolor = c("grey68", "red"))
# {
#   y = df$RES
#   x= df$LOC
#   if(highlight_le){le = fillcolor[as.factor(df$ENRICHMENT)]}else{le = as.factor(df$ENRICHMENT)}
#   maxtop = max(df$RES)
#   minbot = min(df$RES)
#   df$YRUG<-rep((minbot - .1), nrow(df))
#   toPlot<-data.frame(x=x, y=y, le = le, YRUG = df$YRUG)
#   g <- ggplot(toPlot, aes(x = x, y = y)) +
#   {if(line)geom_line(color = "black")}+
#     geom_hline(yintercept = 0, colour = "black") +
#     {if(highlight_le) geom_point(size = size, shape=21, fill = le, color = dotcolor) } +
#     {if(!highlight_le) geom_point(size = size, shape=21, fill = fillcolor[1], color = dotcolor) } +
#     #geom_hline(yintercept = maxtop, colour = "red", linetype = "dashed") +
#     #geom_hline(yintercept = minbot, colour = "red", linetype = "dashed") +
#     theme_bw() +
#     {if(rug && highlight_le) geom_point(aes(x=x, y=YRUG, size=le, color = le), shape=124)}+
#     {if(rug && !isTRUE(highlight_le) ) geom_point(aes(x=x, y=YRUG, color = fillcolor[1]), shape=124)}+
#     scale_color_manual(values = fillcolor, guide =FALSE)+
#     theme(panel.border = element_blank(), panel.grid.minor = element_blank()) +
#     labs(x = "Rank", y = "Enrichment Score")+
#     theme(legend.position="none")
#   g
# }
#
#
#
#
#
#
#
#
scfurl/probedeeper documentation built on Oct. 1, 2018, 3:33 a.m.