--- a/plotheatmap.xml	Wed Jul 12 14:29:51 2017 -0400
+++ b/plotheatmap.xml	Mon Feb 24 11:03:02 2025 +0000
@@ -1,5 +1,5 @@
-<tool id="plotheatmap" name="plotHeatmap" version="1.0">
-    <description>Plot heatmap</description>
+<tool id="plotheatmap" name="Plot heatmap" version="1.0">
+    <description>of gene expression data</description>
     <requirements>
         <requirement type="package" version="1.34.0">bioconductor-preprocesscore</requirement>
         <requirement type="package" version="3.0.1">r-gplots</requirement>

--- a/script.R	Wed Jul 12 14:29:51 2017 -0400
+++ b/script.R	Mon Feb 24 11:03:02 2025 +0000
@@ -1,91 +1,94 @@
 #!/usr/bin/env Rscript
 
-args = commandArgs(TRUE)
-countDataPath = args[1]
-statsDataPath = args[2]
-logFC = args[3]
-logCPM = args[4]
-pValue = args[5]
-fdr = args[6]
+args <- commandArgs(TRUE)
+countDataPath <- args[1]
+statsDataPath <- args[2]
+logFC <- args[3]
+logCPM <- args[4]
+pValue <- args[5]
+fdr <- args[6]
 
-clusterRow = args[7]
-clusterCol = args[8]
-hclustMethod = args[9]
+clusterRow <- args[7]
+clusterCol <- args[8]
+hclustMethod <- args[9]
 
-mgColumnNm = as.numeric(args[10])
-mgRowNm = as.numeric(args[11])
+mgColumnNm <- as.numeric(args[10])
+mgRowNm <- as.numeric(args[11])
 
-pdfWidth = as.numeric(args[12])
-pdfHeight = as.numeric(args[13])
+pdfWidth <- as.numeric(args[12])
+pdfHeight <- as.numeric(args[13])
 
 
-if(clusterRow == "Yes"){
-  clusterRow = TRUE
+if (clusterRow == "Yes") {
+    clusterRow <- TRUE
 } else {
-  clusterRow = NA
+    clusterRow <- NA
 }
 
-if(clusterCol == "Yes"){
-  clusterCol = TRUE
+if (clusterCol == "Yes") {
+    clusterCol <- TRUE
 } else {
-  clusterCol = NA
+    clusterCol <- NA
 }
 
 require(preprocessCore)
 require(gplots)
 
-#prepare counts data --------------------------------------------------------
-countData = read.table(countDataPath, comment = "",
-                       sep = "\t")
+# prepare counts data --------------------------------------------------------
+countData <- read.table(countDataPath,
+    comment = "",
+    sep = "\t"
+)
 
-groups = sapply(as.character(countData[1, -1]), strsplit, ":")
-groups = as.vector(t(countData[1, -1]))
+groups <- sapply(as.character(countData[1, -1]), strsplit, ":")
+groups <- as.vector(t(countData[1, -1]))
 
-names = as.vector(t(countData[2, -1]))
+names <- as.vector(t(countData[2, -1]))
 
-countData = countData[-c(1,2), ]
-rownames(countData) = countData[, 1]
-countData = countData[, -1]
-colnames(countData) = names
+countData <- countData[-c(1, 2), ]
+rownames(countData) <- countData[, 1]
+countData <- countData[, -1]
+colnames(countData) <- names
 
-countData = countData[, order(groups, names)]
+countData <- countData[, order(groups, names)]
 
 # prepare stats data ------------------------------------------------------
 
-statsData = read.table(statsDataPath, sep = "\t",
-                       header = T)
+statsData <- read.table(statsDataPath,
+    sep = "\t",
+    header = T
+)
 
-colnames(statsData)[-1] = sapply(colnames(statsData)[-1], function(x){
-  unlist(strsplit(x, ".", fixed = T))[3]
+colnames(statsData)[-1] <- sapply(colnames(statsData)[-1], function(x) {
+    unlist(strsplit(x, ".", fixed = T))[3]
 })
 
-wh = which(abs(statsData$logFC) >= logFC & statsData$logCPM >= logCPM & statsData$PValue <= pValue & statsData$FDR <= fdr)
+wh <- which(abs(statsData$logFC) >= logFC & statsData$logCPM >= logCPM & statsData$PValue <= pValue & statsData$FDR <= fdr)
 
-for(i in 1:ncol(countData)){
-  countData[,i] = as.numeric(countData[,i])
+for (i in 1:ncol(countData)) {
+    countData[, i] <- as.numeric(countData[, i])
 }
 
-countDataNorm = normalize.quantiles(as.matrix(countData), copy = T)
-countDataNormLog = log(countDataNorm + 1, 2)
+countDataNorm <- normalize.quantiles(as.matrix(countData), copy = T)
+countDataNormLog <- log(countDataNorm + 1, 2)
 
-colnames(countDataNormLog) = colnames(countData)
-rownames(countDataNormLog) = rownames(countData)
+colnames(countDataNormLog) <- colnames(countData)
+rownames(countDataNormLog) <- rownames(countData)
 
-#svg("heatmap.svg", width = 3+length(names), height = 1/2*length(wh))
+# svg("heatmap.svg", width = 3+length(names), height = 1/2*length(wh))
 pdf("heatmap.pdf", width = pdfWidth, height = pdfHeight)
 
 heatmap.2(
-  countDataNormLog[wh, ],
-  density.info=c("none"),
-  hclustfun = function(x) hclust(x, method = hclustMethod),
-  distfun = function(x) as.dist(1-cor(t(x))),  
-  col = bluered(50), 
-  scale = "row", 
-  trace = "none", 
-  Rowv = clusterRow, 
-  Colv = clusterCol,
-  margins = c(mgColumnNm, mgRowNm)
+    countDataNormLog[wh, ],
+    density.info = c("none"),
+    hclustfun = function(x) hclust(x, method = hclustMethod),
+    distfun = function(x) as.dist(1 - cor(t(x))),
+    col = bluered(50),
+    scale = "row",
+    trace = "none",
+    Rowv = clusterRow,
+    Colv = clusterCol,
+    margins = c(mgColumnNm, mgRowNm)
 )
 
 dev.off()
-