## Setup R error handling to go to stderr
options(show.error.messages = FALSE, error = function() {
  cat(geterrmessage(), file = stderr())
  q("no", 1, FALSE)
})
# we need that to not crash galaxy with an UTF8 error on German LC settings.
Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")

suppressPackageStartupMessages({
  library("getopt")
  library("DiffBind")
  library("rjson")
})

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).
spec <- matrix(c(
  "infile", "i", 1, "character",
  "outfile", "o", 1, "character",
  "scorecol", "n", 1, "integer",
  "lowerbetter", "l", 1, "logical",
  "summits", "s", 1, "integer",
  "th", "t", 1, "double",
  "format", "f", 1, "character",
  "plots", "p", 2, "character",
  "bmatrix", "b", 0, "logical",
  "rdaOpt", "r", 0, "logical",
  "infoOpt", "a", 0, "logical",
  "verbose", "v", 2, "integer",
  "help", "h", 0, "logical"
), byrow = TRUE, ncol = 4)

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)
}

parser <- newJSONParser()
parser$addData(opt$infile)
factor_list <- parser$getObject()
filenames_in <- unname(unlist(factor_list[[1]][[2]]))
peaks <- filenames_in[grepl("peaks.bed", filenames_in)]
bams <- filenames_in[grepl("bamreads.bam", filenames_in)]
ctrls <- filenames_in[grepl("bamcontrol.bam", filenames_in)]

# get the group and sample id from the peaks filenames
groups <- sapply(strsplit(peaks, "-"), `[`, 1)
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
} else {
  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)

if (!is.null(opt$summits)) {
  sample_count <- dba.count(sample, summits = opt$summits)
} else {
  sample_count <- dba.count(sample)
}

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)

# 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)
  dev.off()
}

# Output differential binding sites
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),
    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))
  )
} else if (opt$format == "interval") {
  # Output as interval
  df <- as.data.frame(res_sorted)
  extrainfo <- NULL
  for (i in seq_len(nrow(df))) {
    extrainfo[i] <- paste0(c(df$width[i], df[i, 6:ncol(df)]), collapse = "|")
  }
  res_sorted  <- data.frame(
    Chrom = seqnames(res_sorted),
    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
  )
} else {
  # Output as 0-based tabular
  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)
  )
}
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)
  # Output as 0-based tabular
  bmat <- data.frame(
    Chrom = bmat[, 1],
    Start = bmat[, 2] - 1,
    End = bmat[, 3],
    bmat[, 4:ncol(bmat)]
  )
  write.table(bmat, file = "bmatrix.tab", sep = "\t", quote = FALSE, row.names = FALSE)
}

# Output RData file
if (!is.null(opt$rdaOpt)) {
  save.image(file = "DiffBind_analysis.RData")
}

# Output analysis info
if (!is.null(opt$infoOpt)) {
  info <- "DiffBind_analysis_info.txt"
  cat("dba.count Info\n\n", file = info, append = TRUE)
  capture.output(sample, file = info, append = TRUE)
  cat("\ndba.analyze Info\n\n", file = info, append = TRUE)
  capture.output(sample_analyze, file = info, append = TRUE)
  cat("\nSessionInfo\n\n", file = info, append = TRUE)
  capture.output(sessionInfo(), file = info, append = TRUE)
}