--- a/egsea.R	Sat Feb 09 09:15:52 2019 -0500
+++ b/egsea.R	Mon Jun 28 09:45:14 2021 +0000
@@ -1,6 +1,8 @@
 # Code based on (and inspired by) the Galaxy limma-voom/edgeR/DESeq2 wrappers
 
-options( show.error.messages=F, error = function () { cat( geterrmessage(), file=stderr() ); q( "no", 1, F ) } )
+options(show.error.messages = F, error = function() {
+    cat(geterrmessage(), file = stderr()); q("no", 1, F)
+})
 
 # we need that to not crash galaxy with an UTF8 error on German LC settings.
 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
@@ -15,7 +17,7 @@
 
 ## Function Declaration
 
-sanitiseEquation <- function(equation) {
+sanitise_equation <- function(equation) {
     equation <- gsub(" *[+] *", "+", equation)
     equation <- gsub(" *[-] *", "-", equation)
     equation <- gsub(" *[/] *", "/", equation)
@@ -25,43 +27,43 @@
 }
 
 # Function to sanitise group information
-sanitiseGroups <- function(string) {
+sanitise_groups <- function(string) {
     string <- gsub(" *[,] *", ",", string)
     string <- gsub("^\\s+|\\s+$", "", string)
     return(string)
 }
 
 # Generating design information
-pasteListName <- function(string) {
+paste_listname <- function(string) {
     return(paste0("factors$", string))
 }
 
 ## Input Processing
 
 option_list <- list(
-    make_option(c("-threads", "--threads"), default=2, type="integer", help="Number of threads for egsea"),
-    make_option(c("-filesPath", "--filesPath"), type="character", help="JSON list object if multiple files input"),
-    make_option(c("-matrixPath", "--matrixPath"), type="character", help="Path to count matrix"),
-    make_option(c("-factFile", "--factFile"), type="character", help="Path to factor information file"),
-    make_option(c("-factInput", "--factInput"), type="character", help="String containing factors if manually input"),
-    make_option(c("-contrastData", "--contrastData"), type="character", help="Contrasts of Interest (Groups to compare)"),
-    make_option(c("-genes", "--genes"), type="character", help="Path to genes file"),
-    make_option(c("-species", "--species"), type="character"),
-    make_option(c("-base_methods", "--base_methods"), type="character", help="Gene set testing methods"),
-    make_option(c("-msigdb", "--msigdb"), type="character", help="MSigDB Gene Set Collections"),
-    make_option(c("-keggdb", "--keggdb"), type="character", help="KEGG Pathways"),
-    make_option(c("-keggupdated", "--keggupdated"), type="logical", help="Use updated KEGG"),
-    make_option(c("-gsdb", "--gsdb"), type="character", help = "GeneSetDB Gene Sets"),
-    make_option(c("-display_top", "--display_top"), type="integer", help = "Number of top Gene Sets to display"),
-    make_option(c("-min_size", "--min_size"), type="integer", help = "Minimum Size of Gene Set"),
-    make_option(c("-fdr_cutoff", "--fdr_cutoff"), type="double", help = "FDR cutoff"),
-    make_option(c("-combine_method", "--combine_method"), type="character", help="Method to use to combine the p-values"),
-    make_option(c("-sort_method", "--sort_method"), type="character", help="Method to sort the results"),
-    make_option(c("-rdaOpt", "--rdaOpt"), type="character", help="Output RData file")
+    make_option("--threads", default = 2, type = "integer", help = "Number of threads for egsea"),
+    make_option("--filesPath", type = "character", help = "JSON list object if multiple files input"),
+    make_option("--matrixPath", type = "character", help = "Path to count matrix"),
+    make_option("--factFile", type = "character", help = "Path to factor information file"),
+    make_option("--factInput", type = "character", help = "String containing factors if manually input"),
+    make_option("--contrastData", type = "character", help = "Contrasts of Interest (Groups to compare)"),
+    make_option("--genes", type = "character", help = "Path to genes file"),
+    make_option("--species", type = "character"),
+    make_option("--base_methods", type = "character", help = "Gene set testing methods"),
+    make_option("--msigdb", type = "character", help = "MSigDB Gene Set Collections"),
+    make_option("--keggdb", type = "character", help = "KEGG Pathways"),
+    make_option("--keggupdated", type = "logical", help = "Use updated KEGG"),
+    make_option("--gsdb", type = "character", help  =  "GeneSetDB Gene Sets"),
+    make_option("--display_top", type = "integer", help  =  "Number of top Gene Sets to display"),
+    make_option("--min_size", type = "integer", help  =  "Minimum Size of Gene Set"),
+    make_option("--fdr_cutoff", type = "double", help  =  "FDR cutoff"),
+    make_option("--combine_method", type = "character", help = "Method to use to combine the p-values"),
+    make_option("--sort_method", type = "character", help = "Method to sort the results"),
+    make_option("--rdaOpt", type = "character", help = "Output RData file")
     )
 
-parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
-args = parse_args(parser)
+parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
+args <- parse_args(parser)
 
 
 ## Read in Files
@@ -71,63 +73,65 @@
     library("rjson")
     parser <- newJSONParser()
     parser$addData(args$filesPath)
-    factorList <- parser$getObject()
-    factors <- sapply(factorList, function(x) x[[1]])
-    filenamesIn <- unname(unlist(factorList[[1]][[2]]))
-    sampleTable <- data.frame(sample=basename(filenamesIn),
-                            filename=filenamesIn,
-                            row.names=filenamesIn,
-                            stringsAsFactors=FALSE)
-    for (factor in factorList) {
-        factorName <- factor[[1]]
-        sampleTable[[factorName]] <- character(nrow(sampleTable))
+    factor_list <- parser$getObject()
+    factors <- sapply(factor_list, function(x) x[[1]])
+    filenames_in <- unname(unlist(factor_list[[1]][[2]]))
+    sampletable <- data.frame(sample = basename(filenames_in),
+                            filename = filenames_in,
+                            row.names = filenames_in,
+                            stringsAsFactors = FALSE)
+    for (factor in factor_list) {
+        factorname <- factor[[1]]
+        sampletable[[factorname]] <- character(nrow(sampletable))
         lvls <- sapply(factor[[2]], function(x) names(x))
         for (i in seq_along(factor[[2]])) {
             files <- factor[[2]][[i]][[1]]
-            sampleTable[files,factorName] <- lvls[i]
+            sampletable[files, factorname] <- lvls[i]
         }
-        sampleTable[[factorName]] <- factor(sampleTable[[factorName]], levels=lvls)
+        sampletable[[factorname]] <- factor(sampletable[[factorname]], levels = lvls)
     }
-    rownames(sampleTable) <- sampleTable$sample
-    rem <- c("sample","filename")
-    factors <- sampleTable[, !(names(sampleTable) %in% rem), drop=FALSE]
+    rownames(sampletable) <- sampletable$sample
+    rem <- c("sample", "filename")
+    factors <- sampletable[, !(names(sampletable) %in% rem), drop = FALSE]
 
     #read in count files and create single table
-    countfiles <- lapply(sampleTable$filename, function(x){read.delim(x, row.names=1)})
+    countfiles <- lapply(sampletable$filename, function(x) {
+        read.delim(x, row.names = 1)
+        })
     counts <- do.call("cbind", countfiles)
 
 } else {
  # Process the single count matrix
-    counts <- read.table(args$matrixPath, header=TRUE, sep="\t", stringsAsFactors=FALSE, check.names=FALSE)
+    counts <- read.table(args$matrixPath, header = TRUE, sep = "\t", stringsAsFactors = FALSE, check.names = FALSE)
     row.names(counts) <- counts[, 1]
-    counts <- counts[ , -1]
-    countsRows <- nrow(counts)
+    counts <- counts[, -1]
+    countsrows <- nrow(counts)
 
     # Process factors
     if (is.null(args$factInput)) {
-            factorData <- read.table(args$factFile, header=TRUE, sep="\t", strip.white=TRUE)
+            factordata <- read.table(args$factFile, header = TRUE, sep = "\t", strip.white = TRUE, stringsAsFactors = TRUE)
             # check samples names match
-            if(!any(factorData[, 1] %in% colnames(counts)))
+            if (!any(factordata[, 1] %in% colnames(counts)))
                 stop("Sample IDs in factors file and count matrix don't match")
             # order samples as in counts matrix
-            factorData <- factorData[match(colnames(counts), factorData[, 1]), ]
-            factors <- factorData[, -1, drop=FALSE]
+            factordata <- factordata[match(colnames(counts), factordata[, 1]), ]
+            factors <- factordata[, -1, drop = FALSE]
     }  else {
-            factors <- unlist(strsplit(args$factInput, "|", fixed=TRUE))
-            factorData <- list()
+            factors <- unlist(strsplit(args$factInput, "|", fixed = TRUE))
+            factordata <- list()
             for (fact in factors) {
-                newFact <- unlist(strsplit(fact, split="::"))
-                factorData <- rbind(factorData, newFact)
+                newfact <- unlist(strsplit(fact, split = "::"))
+                factordata <- rbind(factordata, newfact)
             } # Factors have the form: FACT_NAME::LEVEL,LEVEL,LEVEL,LEVEL,... The first factor is the Primary Factor.
 
             # Set the row names to be the name of the factor and delete first row
-            row.names(factorData) <- factorData[, 1]
-            factorData <- factorData[, -1]
-            factorData <- sapply(factorData, sanitiseGroups)
-            factorData <- sapply(factorData, strsplit, split=",")
-            factorData <- sapply(factorData, make.names)
+            row.names(factordata) <- factordata[, 1]
+            factordata <- factordata[, -1]
+            factordata <- sapply(factordata, sanitise_groups)
+            factordata <- sapply(factordata, strsplit, split = ",")
+            factordata <- sapply(factordata, make.names)
             # Transform factor data into data frame of R factor objects
-            factors <- data.frame(factorData)
+            factors <- data.frame(factordata, stringsAsFactors = TRUE)
     }
 }
 
@@ -135,36 +139,36 @@
 counts <- DGEList(counts)
 
 # Set group to be the Primary Factor input
-group <- factors[, 1, drop=FALSE]
+group <- factors[, 1, drop = FALSE]
 
 # Split up contrasts separated by comma into a vector then sanitise
-contrastData <- unlist(strsplit(args$contrastData, split=","))
-contrastData <- sanitiseEquation(contrastData)
-contrastData <- gsub(" ", ".", contrastData, fixed=TRUE)
+contrast_data <- unlist(strsplit(args$contrastData, split = ","))
+contrast_data <- sanitise_equation(contrast_data)
+contrast_data <- gsub(" ", ".", contrast_data, fixed = TRUE)
 
 # Creating design
 row.names(factors) <- colnames(counts)
-factorList <- sapply(names(factors), pasteListName)
+factor_list <- sapply(names(factors), paste_listname)
 
 formula <- "~0"
-for (i in 1:length(factorList)) {
-    formula <- paste(formula, factorList[i], sep="+")
+for (i in seq_along(factor_list)) {
+    formula <- paste(formula, factor_list[i], sep = "+")
 }
 formula <- formula(formula)
 
 design <- model.matrix(formula)
 
-for (i in 1:length(factorList)) {
-    colnames(design) <- gsub(factorList[i], "", colnames(design), fixed=TRUE)
+for (i in seq_along(factor_list)) {
+    colnames(design) <- gsub(factor_list[i], "", colnames(design), fixed = TRUE)
 }
 
 ## Generate Contrasts information
-contrasts <- makeContrasts(contrasts=contrastData, levels=design)
+contrasts <- makeContrasts(contrasts = contrast_data, levels = design)
 
 
 ## Add Gene Symbol information
 
-genes <- read.table(args$genes, sep='\t', header=TRUE)
+genes <- read.table(args$genes, sep = "\t", header = TRUE)
 
 
 ## Set Gene Set Testing Methods
@@ -182,7 +186,7 @@
 
 if (args$keggdb != "None") {
     keggdb <- unlist(strsplit(args$keggdb, ","))
-    kegg_all <- c("Metabolism"="keggmet", "Signaling"="keggsig", "Disease"="keggdis")
+    kegg_all <- c("Metabolism" = "keggmet", "Signaling" = "keggsig", "Disease" = "keggdis")
     kegg_exclude <- names(kegg_all[!(kegg_all %in% keggdb)])
 } else {
     kegg_exclude <- "all"
@@ -196,16 +200,16 @@
 
 ## Index gene sets
 
-gs.annots <- buildIdx(entrezIDs=rownames(counts), species=args$species, msigdb.gsets=msigdb, gsdb.gsets=gsdb, kegg.exclude=kegg_exclude, kegg.updated=args$keggupdated)
+gs_annots <- buildIdx(entrezIDs = rownames(counts), species = args$species, msigdb.gsets = msigdb, gsdb.gsets = gsdb, kegg.exclude = kegg_exclude, kegg.updated = args$keggupdated)
 
 
 ## Run egsea.cnt
 
-gsa <- egsea.cnt(counts=counts, group=group, design=design, contrasts=contrasts, gs.annots=gs.annots, symbolsMap=genes, baseGSEAs=base_methods, minSize=args$min_size, display.top=args$display_top, combineMethod=args$combine_method, sort.by=args$sort_method, report.dir='./report_dir', fdr.cutoff=args$fdr_cutoff, num.threads=args$threads, report=TRUE)
+gsa <- egsea.cnt(counts = counts, group = group, design = design, contrasts = contrasts, gs.annots = gs_annots, symbolsMap = genes, baseGSEAs = base_methods, minSize = args$min_size, display.top = args$display_top, combineMethod = args$combine_method, sort.by = args$sort_method, report.dir = "./report_dir", fdr.cutoff = args$fdr_cutoff, num.threads = args$threads, report = TRUE)
 
 
 ## Output RData file
 
 if (!is.null(args$rdaOpt)) {
   save.image(file = "EGSEA_analysis.RData")
-}
\ No newline at end of file
+}