R/pairwiseMatrixOfEnrichments.R

In Sage-Bionetworks/AMPAD:

pairwiseMatrixOfEnrichments = function(synId,outputFile=FALSE,fileName1='figure1b.tiff'){

  ##pull aggregate modules
  #aggregateModules <- rSynapseUtilities::loadFullTable(synId)
  aggregateModules <- synapser::synTableQuery(paste0("select * from ",synId))$asDataFrame()
  aggregateModules <- aggregateModules[,-c(1,2)]

  #View(aggregateModules)

  mats <- AMPAD::computePairwiseMatrixOfEnrichments(key=aggregateModules$Module,
                                                        value=aggregateModules$GeneID)


  customDf <- data.frame(moduleName=c('TCXblue',
                                      'IFGyellow',
                                      'PHGyellow',
                                      'DLPFCblue',
                                      'CBEturquoise',
                                      'STGblue',
                                      'PHGturquoise',
                                      'IFGturquoise',
                                      'TCXturquoise',
                                      'FPturquoise',
                                      'IFGbrown',
                                      'STGbrown',
                                      'DLPFCyellow',
                                      'TCXgreen',
                                      'FPyellow',
                                      'CBEyellow',
                                      'PHGbrown',
                                      'DLPFCbrown',
                                      'STGyellow',
                                      'PHGgreen',
                                      'CBEbrown',
                                      'TCXyellow',
                                      'IFGblue',
                                      'FPblue',
                                      'FPbrown',
                                      'CBEblue',
                                      'DLPFCturquoise',
                                      'TCXbrown',
                                      'STGturquoise',
                                      'PHGblue'),
                         Cluster= c(rep('Consensus Cluster A',3),
                                       rep('Consensus Cluster B',7),
                                       rep('Consensus Cluster C',7),
                                       rep('Consensus Cluster D',7),
                                       rep('Consensus Cluster E',6)),
                         stringsAsFactors=F)
  rownames(customDf) <- customDf$moduleName
  customDf <- dplyr::select(customDf,Cluster)
  #get rid of underflow issues
  #red,yellow,green,blue,purple
  mats$pval <- mats$pval + 1e-300
  if(outputFile){
    tiff(filename=fileName1,height=85,width=85,units='mm',res=300)
    ann_colors<-list(Cluster=c(`Consensus Cluster A`='#fefd11',
                               `Consensus Cluster B`='#18bebf',
                               `Consensus Cluster C`='#a82828',
                               `Consensus Cluster D`='#34cc37',
                               `Consensus Cluster E`='#470606'))
    pheatmap::pheatmap(-log10(mats$pval),
                       show_colnames = F,
                       border_color = NA,
                       fontsize=4,
                       treeheight_row=10,
                       treeheight_col=10,
                       annotation_col = customDf,
                       annotation_colors = ann_colors[1])
    dev.off()
  } else{
    ann_colors<-list(Cluster=c(`Consensus Cluster A`='#fefd11',
                               `Consensus Cluster B`='#18bebf',
                               `Consensus Cluster C`='#a82828',
                               `Consensus Cluster D`='#34cc37',
                               `Consensus Cluster E`='#470606'))
    pheatmap::pheatmap(-log10(mats$pval),
                       show_colnames = F,
                       border_color = NA,
                       fontsize=4,
                       treeheight_row=10,
                       treeheight_col=10,
                       annotation_col = customDf,
                       annotation_colors = ann_colors[1])
  }
}