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")

suppressPackageStartupMessages({
    library("goseq")
    library("optparse")
})

option_list <- list(
    make_option(c("-d", "--dge_file"), type="character", help="Path to file with differential gene expression result"),
    make_option(c("-w","--wallenius_tab"), type="character", help="Path to output file with P-values estimated using wallenius distribution."),
    make_option(c("-s","--sampling_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using wallenius distribution."),
    make_option(c("-n","--nobias_tab"), type="character", default=FALSE, help="Path to output file with P-values estimated using wallenius distribution and no correction for gene length bias."),
    make_option(c("-l","--length_bias_plot"), type="character", default=FALSE, help="Path to length-bias plot."),
    make_option(c("-sw","--sample_vs_wallenius_plot"), type="character", default=FALSE, help="Path to plot comparing sampling with wallenius p-values."),
    make_option(c("-padj", "--p_adj_column"), type="integer",help="Column that contains p. adjust values"),
    make_option(c("-c", "--cutoff"), type="double",dest="p_adj_cutoff",
                help="Genes with p.adjust below cutoff are considered not differentially expressed and serve as control genes"),
    make_option(c("-r", "--repcnt"), type="integer", default=100, help="Number of repeats for sampling"),
    make_option(c("-lf", "--length_file"), type="character", default="FALSE", help = "Path to tabular file mapping gene id to length"),
    make_option(c("-cat_file", "--category_file"), default="FALSE", type="character", help = "Path to tabular file with gene_id <-> category mapping."),
    make_option(c("-g", "--genome"), default=NULL, type="character", help = "Genome [used for looking up correct gene length]"),
    make_option(c("-i", "--gene_id"), default=NULL, type="character", help = "Gene ID format of genes in DGE file"),
    make_option(c("-cat", "--use_genes_without_cat"), default=FALSE, type="logical",
                help="A large number of gene may have no GO term annotated. If this option is set to FALSE, genes without category will be ignored in the calculation of p-values(default behaviour). If TRUE these genes will count towards the total number of genes outside the tested category (default behaviour prior to version 1.15.2)."),
    make_option(c("-plots", "--make_plots"), default=FALSE, type="logical", help="produce diagnostic plots?")
    )

parser <- OptionParser(usage = "%prog [options] file", option_list=option_list)
args = parse_args(parser)

# Vars:
dge_file = args$dge_file
category_file = args$category_file
p_adj_column = args$p_adj_colum
p_adj_cutoff = args$p_adj_cutoff
length_file = args$length_file
genome = args$genome
gene_id = args$gene_id
wallenius_tab = args$wallenius_tab
sampling_tab = args$sampling_tab
nobias_tab = args$nobias_tab
length_bias_plot = args$length_bias_plot
sample_vs_wallenius_plot = args$sample_vs_wallenius_plot
repcnt = args$repcnt
use_genes_without_cat = args$use_genes_without_cat
make_plots = args$make_plots

# format DE genes into named vector suitable for goseq
first_line = read.delim(dge_file, header = FALSE, nrow=1)
# check if header [character where numeric is expected]
if (is.numeric(first_line[,p_adj_column])) {
  dge_table = read.delim(dge_file, header = FALSE, sep="\t")
  } else {
  dge_table = read.delim(dge_file, header = TRUE, sep="\t")
  }

genes = as.integer(dge_table[,p_adj_column]<p_adj_cutoff)
names(genes) = dge_table[,1] # Assuming first row contains gene names

# gene lengths, assuming last column
if (length_file != "FALSE" ) {
  first_line = read.delim(dge_file, header = FALSE, nrow=1)
  if (is.numeric(first_line[, ncol(first_line)])) {
    length_table = read.delim(length_file, header=FALSE, sep="\t", check.names=FALSE)
    } else {
    length_table = read.delim(length_file, header=TRUE, sep="\t", check.names=FALSE)
    }
  row.names(length_table) = length_table[,1]
  gene_lengths = length_table[names(genes),][,ncol(length_table)]
  } else {
  gene_lengths = getlength(names(genes), genome, gene_id)
  }

# Estimate PWF

if (make_plots == TRUE) {
  pdf(length_bias_plot)
}
pwf=nullp(genes, genome = genome, id = gene_id, bias.data = gene_lengths, plot.fit=make_plots)
graphics.off()

# Fetch GO annotations if category_file hasn't been supplied:
if (category_file == "FALSE") {
  go_map=getgo(genes = names(genes), genome = genome, id = gene_id, fetch.cats=c("GO:CC", "GO:BP", "GO:MF", "KEGG"))
  } else {
  # check for header: first entry in first column must be present in genes, else it's a header
  first_line = read.delim(category_file, header = FALSE, nrow=1)
  if (first_line[,1] %in% names(genes)) {
     go_map = read.delim(category_file, header = FALSE)
     } else {
     go_map = read.delim(category_file, header= TRUE)
    }
}

# wallenius approximation of p-values
GO.wall=goseq(pwf, genome = genome, id = gene_id, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)

GO.nobias=goseq(pwf, genome = genome, id = gene_id, method="Hypergeometric", use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)

# Sampling distribution
if (repcnt > 0) {
  GO.samp=goseq(pwf, genome = genome, id = gene_id, method="Sampling", repcnt=repcnt, use_genes_without_cat = use_genes_without_cat, gene2cat=go_map)
  # Compare sampling with wallenius
  if (make_plots == TRUE) {
  pdf(sample_vs_wallenius_plot)
  plot(log10(GO.wall[,2]), log10(GO.samp[match(GO.samp[,1],GO.wall[,1]),2]),
     xlab="log10(Wallenius p-values)",ylab="log10(Sampling p-values)",
     xlim=c(-3,0))
     abline(0,1,col=3,lty=2)
  graphics.off()
  }
  write.table(GO.samp, sampling_tab, sep="\t", row.names = FALSE, quote = FALSE)
}


write.table(GO.wall, wallenius_tab, sep="\t", row.names = FALSE, quote = FALSE)
write.table(GO.nobias, nobias_tab, sep="\t", row.names = FALSE, quote = FALSE)

sessionInfo()

# Use the following to get a list of supported genomes / gene ids

# write.table(supportedGenomes(), "available_genomes.tab", row.names = FALSE, quote=FALSE)
# write.table(supportedGeneIDs(), "supported_gene_ids.tab", row.name = FALSE, quote = FALSE)
# write.table(table.summary, "input_gene_count_matrix.tab", row.names = FALSE, quote = FALSE)