#!/usr/bin/env perl

use Getopt::Long;
use Pod::Usage;
use strict;

my $hard = 0;
my $soft = 0;
my $help = 0;

GetOptions("hard-threshold" => \$hard,
	   "soft-threshold" => \$soft,
	   "h|help" => \$help) or pod2usage(-exitval => 2, -verbose => 2);

pod2usage(-verbose => 2) if ($help == 1);
pod2usage(-msg => "Invalid number of arguments!", -exitval => 2, -verbose => 2) if (scalar(@ARGV) != 3);
pod2usage(-msg => "--hard-threshold and --soft-threshold cannot be set at the same time!", -exitval => 2, -verbose => 2) if ($hard && $soft);

if ($hard == 0 && $soft == 0) { $hard = 1; }

my $fdr = $ARGV[1];

open(INPUT, "$ARGV[0]");
open(OUTPUT, ">$ARGV[2]");

my $header = <INPUT>;
chomp($header);
my @columns = split(/\t/, $header);

my $pos = 0;
while ($pos <= $#columns && $columns[$pos] ne "\"PPDE\"") { ++$pos; }
if ($pos > $#columns) { print "Error: Cannot find column PPDE!\n"; exit(-1); }
++$pos;

print OUTPUT "$header\n";

my ($n, $sum) = (0, 0);
my $line = "";
while($line = <INPUT>) {
    chomp($line);
    my @fields = split(/\t/, $line);
    my $ppee = 1.0 - $fields[$pos];
    if ($hard) {
	if ($ppee > $fdr) { last; }
	++$n;
	print OUTPUT "$line\n";
    }
    else {
	if ($sum + $ppee > $fdr * ($n + 1)) { last; }
	++$n;
	$sum += $ppee;
	print OUTPUT "$line\n";
    }
}

print "There are $n genes/transcripts reported at FDR = $fdr.\n";

close(INPUT);
close(OUTPUT);

__END__

=head1 NAME

rsem-control-fdr

=head1 SYNOPSIS

rsem-control-fdr [options] input_file fdr_rate output_file

=head1 ARGUMENTS

=over

=item B<input_file>

This should be the main result file generated by 'rsem-run-ebseq', which contains all genes/transcripts and their associated statistics.

=item B<fdr_rate>

The desire false discovery rate (FDR). 

=item B<output_file>

This file is a subset of the 'input_file'. It only contains the genes/transcripts called as differentially expressed (DE). When more than 2 conditions exist, DE is defined as not all conditions are equally expressed.  Because statistical significance does not necessarily mean biological significance, users should also refer to the fold changes to decide which genes/transcripts are biologically significant. When more than two conditions exist, this file will not contain fold change information and users need to calculate it from 'input_file.condmeans' by themselves.

=back

=head1 OPTIONS

=over

=item B<--hard-threshold> 

Use hard threshold method to control FDR. If this option is set, only those genes/transcripts with their PPDE >= 1 - fdr_rate are called as DE. (Default: on)

=item B<--soft-threshold>

Use soft threshold method to control FDR. If this option is set, this program will try to report as many genes/transcripts as possible, as long as their average PPDE >= 1 - fdr_rate. This option is equivalent to use EBSeq's 'crit_fun' for FDR control. (Default: off)

=item B<-h/--help> 

Show help information.

=back

=head1 DESCRIPTION

This program controls the false discovery rate and reports differentially expressed genes/transcripts. 

=head1 EXAMPLES

We assume that we have 'GeneMat.results' as input. We want to control FDR at 0.05 using hard threshold method and name the output file as 'GeneMat.de.txt':

 rsem-control-fdr GeneMat.results 0.05 GeneMat.de.txt

=cut