--- a/diffbind.R	Tue Aug 31 08:02:07 2021 +0000
+++ b/diffbind.R	Mon Jul 08 18:31:37 2024 +0000
@@ -1,6 +1,7 @@
 ## Setup R error handling to go to stderr
 options(show.error.messages = F, error = function() {
-    cat(geterrmessage(), file = stderr()); q("no", 1, F)
+    cat(geterrmessage(), file = stderr())
+    q("no", 1, F)
 })
 # we need that to not crash galaxy with an UTF8 error on German LC settings.
 Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
@@ -14,15 +15,18 @@
 options(stringAsfactors = FALSE, useFancyQuotes = FALSE)
 args <- commandArgs(trailingOnly = TRUE)
 
-#get options, using the spec as defined by the enclosed list.
-#we read the options from the default: commandArgs(TRUE).
+# get options, using the spec as defined by the enclosed list.
+# we read the options from the default: commandArgs(TRUE).
 spec <- matrix(c(
     "infile", "i", 1, "character",
     "outfile", "o", 1, "character",
+    "method", "m", 1, "character",
     "scorecol", "n", 1, "integer",
     "lowerbetter", "l", 1, "logical",
     "summits", "s", 1, "integer",
     "th", "t", 1, "double",
+    "minoverlap", "O", 1, "integer",
+    "use_blacklist", "B", 0, "logical",
     "format", "f", 1, "character",
     "plots", "p", 2, "character",
     "bmatrix", "b", 0, "logical",
@@ -30,15 +34,14 @@
     "infoOpt", "a", 0, "logical",
     "verbose", "v", 2, "integer",
     "help", "h", 0, "logical"
-), byrow = TRUE, ncol = 4);
+), byrow = TRUE, ncol = 4)
 
-opt <- getopt(spec);
-
+opt <- getopt(spec)
 # if help was asked for print a friendly message
 # and exit with a non-zero error code
 if (!is.null(opt$help)) {
-    cat(getopt(spec, usage = TRUE));
-    q(status = 1);
+    cat(getopt(spec, usage = TRUE))
+    q(status = 1)
 }
 
 parser <- newJSONParser()
@@ -54,23 +57,30 @@
 samples <- sapply(strsplit(peaks, "-"), `[`, 2)
 
 if (length(ctrls) != 0) {
-    sample_table <- data.frame(SampleID = samples,
-                        Condition = groups,
-                        bamReads = bams,
-                        bamControl = ctrls,
-                        Peaks = peaks,
-                        Tissue = samples) # using "Tissue" column to display ids as labels in PCA plot
+    sample_table <- data.frame(
+        SampleID = samples,
+        Condition = groups,
+        bamReads = bams,
+        bamControl = ctrls,
+        Peaks = peaks,
+        Tissue = samples
+    ) # using "Tissue" column to display ids as labels in PCA plot
 } else {
-
-    sample_table <- data.frame(SampleID = samples,
-                        Replicate = samples,
-                        Condition = groups,
-                        bamReads = bams,
-                        Peaks = peaks,
-                        Tissue = samples)
+    sample_table <- data.frame(
+        SampleID = samples,
+        Replicate = samples,
+        Condition = groups,
+        bamReads = bams,
+        Peaks = peaks,
+        Tissue = samples
+    )
 }
 
-sample <- dba(sampleSheet = sample_table, peakFormat = "bed", scoreCol = opt$scorecol, bLowerScoreBetter = opt$lowerbetter)
+sample <- dba(sampleSheet = sample_table, peakFormat = "bed", scoreCol = opt$scorecol, bLowerScoreBetter = opt$lowerbetter, minOverlap = opt$minoverlap)
+
+if (!is.null(opt$use_blacklist)) {
+    sample <- dba.blacklist(sample, blacklist = TRUE)
+}
 
 if (!is.null(opt$summits)) {
     sample_count <- dba.count(sample, summits = opt$summits)
@@ -79,17 +89,25 @@
 }
 
 sample_contrast <- dba.contrast(sample_count, categories = DBA_CONDITION, minMembers = 2)
-sample_analyze <- dba.analyze(sample_contrast)
-diff_bind <- dba.report(sample_analyze, th = opt$th)
+
+if (opt$method == "DBA_DESEQ2") {
+    method <- DBA_DESEQ2
+} else if (opt$method == "DBA_EDGER") {
+    method <- DBA_EDGER
+}
+
+sample_analyze <- dba.analyze(sample_contrast, method = method, bBlacklist = FALSE, bGreylist = FALSE)
+
+diff_bind <- dba.report(sample_analyze, th = opt$th, method = method)
 
 # Generate plots
 if (!is.null(opt$plots)) {
     pdf(opt$plots)
-    orvals <- dba.plotHeatmap(sample_analyze, contrast = 1, correlations = FALSE, cexCol = 0.8, th = opt$th)
-    dba.plotPCA(sample_analyze, contrast = 1, th = opt$th, label = DBA_TISSUE, labelSize = 0.3)
-    dba.plotMA(sample_analyze, th = opt$th)
-    dba.plotVolcano(sample_analyze, th = opt$th)
-    dba.plotBox(sample_analyze, th = opt$th)
+    orvals <- dba.plotHeatmap(sample_analyze, contrast = 1, correlations = FALSE, cexCol = 0.8, th = opt$th, method = method)
+    dba.plotPCA(sample_analyze, contrast = 1, th = opt$th, label = DBA_TISSUE, labelSize = 0.3, method = method)
+    dba.plotMA(sample_analyze, th = opt$th, method = method)
+    dba.plotVolcano(sample_analyze, th = opt$th, method = method)
+    dba.plotBox(sample_analyze, th = opt$th, method = method)
     dev.off()
 }
 
@@ -97,46 +115,54 @@
 res_sorted <- diff_bind[order(diff_bind$FDR), ]
 # Convert from GRanges (1-based) to 0-based format (adapted from https://www.biostars.org/p/89341/)
 if (opt$format == "bed") {
-    res_sorted  <- data.frame(Chrom = seqnames(res_sorted),
+    res_sorted <- data.frame(
+        Chrom = seqnames(res_sorted),
         Start = start(res_sorted) - 1,
         End = end(res_sorted),
         Name = rep("DiffBind", length(res_sorted)),
         Score = rep("0", length(res_sorted)),
-        Strand = gsub("\\*", ".", strand(res_sorted)))
+        Strand = gsub("\\*", ".", strand(res_sorted))
+    )
 } else if (opt$format == "interval") {
-     # Output as interval
+    # Output as interval
     df <- as.data.frame(res_sorted)
     extrainfo <- NULL
     for (i in seq_len(nrow(df))) {
         extrainfo[i] <- paste0(c(df$width[i], df[i, 6:ncol(df)]), collapse = "|")
     }
-    res_sorted  <- data.frame(Chrom = seqnames(res_sorted),
+    res_sorted <- data.frame(
+        Chrom = seqnames(res_sorted),
         Start = start(res_sorted) - 1,
         End = end(res_sorted),
         Name = rep("DiffBind", length(res_sorted)),
         Score = rep("0", length(res_sorted)),
         Strand = gsub("\\*", ".", strand(res_sorted)),
-        Comment = extrainfo)
+        Comment = extrainfo
+    )
 } else {
     # Output as 0-based tabular
-    res_sorted <- data.frame(Chrom = seqnames(res_sorted),
+    res_sorted <- data.frame(
+        Chrom = seqnames(res_sorted),
         Start = start(res_sorted) - 1,
         End = end(res_sorted),
         Name = rep("DiffBind", length(res_sorted)),
         Score = rep("0", length(res_sorted)),
         Strand = gsub("\\*", ".", strand(res_sorted)),
-        mcols(res_sorted))
+        mcols(res_sorted)
+    )
 }
 write.table(res_sorted, file = opt$outfile, sep = "\t", quote = FALSE, row.names = FALSE)
 
 # Output binding affinity scores
 if (!is.null(opt$bmatrix)) {
-    bmat <- dba.peakset(sample_count, bRetrieve = TRUE, DataType = DBA_DATA_FRAME)
+    bmat <- dba.peakset(sample_count, bRetrieve = TRUE, DataType = DBA_DATA_FRAME, minOverlap = opt$minoverlap)
     # Output as 0-based tabular
-    bmat <- data.frame(Chrom = bmat[, 1],
+    bmat <- data.frame(
+        Chrom = bmat[, 1],
         Start = bmat[, 2] - 1,
         End = bmat[, 3],
-        bmat[, 4:ncol(bmat)])
+        bmat[, 4:ncol(bmat)]
+    )
     write.table(bmat, file = "bmatrix.tab", sep = "\t", quote = FALSE, row.names = FALSE)
 }