Merge branch 'bridges-compatability' into 'master'

Bridges compatability

Updates so things work on bridges as well as on local submit sites.

See merge request !32

chipathlon/conf.py

@@ -40,6 +40,31 @@ peak_tools = [
     "music"
 ]
 
+executables = [
+    "bedtools",
+    "samtools",
+    "idr",
+    "picard",
+    "bwa",
+    "bowtie2",
+    "macs2",
+    "gem",
+    "peakranger",
+    "MUSIC",
+    "CCAT",
+    "run_spp_nodups",
+    "chip-job-cat-peak",
+    "chip-job-ccat-format-bed",
+    "chip-job-chr-convert",
+    "chip-job-save-result",
+    "chip-job-download-encode",
+    "chip-job-download-gridfs",
+    "chip-job-music",
+    "chip-job-peakranger-format",
+    "chip-job-sort-peak",
+    "chip-job-zcat-peak"
+]
+
 # Peak_type validation
 peak_types = {
     "spp": ["narrow", "broad"],
@@ -152,3 +177,12 @@ genomes = {
         "additional_files": file_extensions["bowtie2_genome"]
     }
 }
+
+config_file = {
+    "required_keys": [
+        "chipathlon_bin", "idr_bin", "pegasus_home", "email"
+    ],
+    "optional_keys": [
+        "arch", "os"
+    ]
+}

chipathlon/jobs/params/cat_awk_sort_peaks.yaml

@@ -8,7 +8,7 @@ cat_awk_sort_peaks:
     - name: sorted_result
       type: file
       file_type: bed
-  command: cat_spp.sh
+  command: chip-job-cat-peak
   arguments:
     - "$inputs.0":
         type: file

chipathlon/jobs/params/ccat_callpeak.yaml

@@ -35,7 +35,7 @@ ccat_callpeak:
     - name: ccat_log
       type: stdout
       file_type: log
-  command: ccat
+  command: CCAT
   arguments:
     - "$inputs.0":
         type: file

chipathlon/jobs/params/ccat_format_bed.yaml

@@ -8,15 +8,15 @@ ccat_format_bed:
     - name: sorted_peaks
       type: file
       file_type: bed
-  command: ccat_format_bed.pl
+  command: chip-job-ccat-format-bed
   arguments:
-    - "-c":
+    - "--input":
         type: file
         changeable: false
         required: true
         has_value: true
         default: $inputs.0
-    - "-b":
+    - "--output":
         type: file
         changeable: false
         required: true

chipathlon/jobs/params/chr_locus_convert.yaml

@@ -8,7 +8,7 @@ chr_locus_convert:
     - name: chr_bed
       type: file
       file_type: bed
-  command: chr_locus_convert.py
+  command: chip-job-chr-convert
   arguments:
     - "-b":
         type: file

chipathlon/jobs/params/db_save_result.yaml

@@ -2,7 +2,7 @@ db_save_result:
   inputs:
     - name: username
       type: string
-      
+
     - name: password
       type: string
 
@@ -18,7 +18,7 @@ db_save_result:
       file_type: yaml
   additional_inputs: null
   outputs: null
-  command: db_save_result.py
+  command: chip-job-save-result
   arguments:
     - "-u":
         type: string

chipathlon/jobs/params/download_from_encode.yaml

@@ -10,7 +10,7 @@ download_from_encode:
     - name: downloaded_file
       type: file
       file_type: any
-  command: download_from_encode.py
+  command: chip-job-download-encode
   arguments:
     - "-u":
         type: string

chipathlon/jobs/params/download_from_gridfs.yaml

@@ -16,7 +16,7 @@ download_from_gridfs:
     - name: downloaded_result
       type: file
       file_type: any
-  command: download_from_gridfs.py
+  command: chip-job-download-gridfs
   arguments:
     - "-H":
         type: string

chipathlon/jobs/params/music_broad.yaml

@@ -42,7 +42,7 @@ music_broad:
     - name: scale_16626.bed
       type: file
       file_type: bed
-  command: music
+  command: chip-job-music
   arguments:
     - "--prefix":
         type: string

chipathlon/jobs/params/music_narrow.yaml

@@ -26,7 +26,7 @@ music_narrow:
     - name: scale_291.bed
       type: file
       file_type: bed
-  command: music
+  command: chip-job-music
   arguments:
     - "--prefix":
         type: string

chipathlon/jobs/params/music_punctate.yaml

@@ -46,7 +46,7 @@ music_punctate:
     - name: scale_2216.bed
       type: file
       file_type: bed
-  command: music
+  command: MUSIC
   arguments:
     - "--prefix":
         type: string

chipathlon/jobs/params/peakranger_format_bed.yaml

@@ -8,15 +8,15 @@ peakranger_format_bed:
     - name: sorted_peaks
       type: file
       file_type: bed
-  command: peakranger_format_bed.pl
+  command: chip-job-peakranger-format
   arguments:
-    - "-c":
+    - "--input":
         type: file
         changeable: false
         required: true
         has_value: true
         default: $inputs.0
-    - "-b":
+    - "--output":
         type: file
         changeable: false
         required: true

chipathlon/jobs/params/sort_awk_sort_peaks.yaml

@@ -8,7 +8,7 @@ sort_awk_sort_peaks:
     - name: sorted_peaks
       type: file
       file_type: bed
-  command: sort_peak.sh
+  command: chip-job-sort-peak
   arguments:
     - "$inputs.0":
         type: file

chipathlon/jobs/params/spp_nodups_broad.yaml

@@ -20,7 +20,7 @@ spp_nodups_broad:
     - name: score
       type: file
       file_type: ccscore
-  command: spp_nodups
+  command: run_spp_nodups
   arguments:
     - "-c=":
         type: file

chipathlon/jobs/params/spp_nodups_narrow.yaml

@@ -20,7 +20,7 @@ spp_nodups_narrow:
     - name: score
       type: file
       file_type: ccscore
-  command: spp_nodups
+  command: run_spp_nodups
   arguments:
     - "-c=":
         type: file

chipathlon/jobs/params/zcat_awk_sort_peaks.yaml

@@ -8,7 +8,7 @@ zcat_awk_sort_peaks:
     - name: sorted_peaks
       type: file
       file_type: bed
-  command: zcat_spp.sh
+  command: chip-job-zcat-peak
   arguments:
     - "$inputs.0":
         type: file

chipathlon/jobs/scripts/V3_csaw_rscript_yaml.R

-#args <- getArgs(defaults=list(workdir=NULL, exper.bams=NULL,control.bams="", 
-#                              analysisID=NULL, exper.dir="./", control.dir="./",
-#                              tf=NULL,cond1=NULL,cond2=NULL,
-#                              orgn=NULL, samples=NULL, contrast=NULL,
-#                              bin.win=10000, blacklist.regions="",
-#                              FDR=0.05, frag.len=10, min.quality=30, paired=FALSE,  
-#                              spacing=50, tol=100, win.width=10))
-
-#print(args)
-commandArgs(trailingOnly = FALSE)
-yamlfile <- '~/Documents/R/csaw_test.yaml'
-library(yaml)
-cat("yamlfile: ", yamlfile)
-pars <- yaml.load_file(yamlfile)
-names(pars)
-# partly based on https://www.bioconductor.org/help/course-materials/2015/BioC2015/csaw_lab.html
-# an example call:
-# where experiments came from GSE25532:
-# A.  K.  Tiwari,  M.  B.  Stadler,  C.  Wirbelauer,  R.  Paro,  D.  Schubeler,  and  C.  Beisel.
-# A chromatin-modifying function of JNK during stem cell dfferentiation.
-# Nat. Genet., 44(1): 94-100, Jan 2012
-
-#yaml.load_file( foo.yml )
-
-outfileStem <- paste0(c(pars$analysisID, pars$tf, pars$cond1.cell, pars$cond2.cell, pars$orgn), collapse="_")
-outfileSimes<-paste0(c(outfileStem,'Simes.txt'), collapse="_")
-outfileBestTest<-paste0(c(outfileStem,'bestTest.txt'), collapse="_")
-cat( "Simes outfile: ", outfileSimes, " bestTestoutfile: ", outfileBestTest, "\n" )
-
-source("https://bioconductor.org/biocLite.R")
-setwd(pars$workdir)
-
-bam.files <- file.path(pars$exper.dir, pars$exper.bams)
-cat("bam.files:\n")
-bam.files
-
-if ( length(pars$control.bams) > 1){
-  control.bams <- file.path(pars$control.dir, pars$control.bams)
-  cat("Control (input) bam(s): ", control.bams, "\n" )
-}
-samples <- pars$samples
-cat("Samples: ", samples, "\n" )
-contrasts<-pars$contrast
-cat("Contrasts: ", contrasts, "\n" )
-# the blacklisted genomic regions
-library(GenomicRanges)
-if ( length(pars$blacklist.regions) > 1){
-  blacklist.regions <- pars$blacklist.regions
-} else {
-  if ( pars$orgn == 'human'){
-    
-  } else {
-    if ( pars$orgn == 'mouse'){
-     
-    } else {
-      cat("Organism: ", pars$orgn, "not implemented yet, only human and mouse\n")
-      quit()
-    }
-  }
-}
-
-library(csaw)
-library(DESeq2)
-require(edgeR)
-param <- readParam(minq=pars$min.quality)
-#Reads are directionally extended to the average fragment length, 
-#to represent the original fragments that were present during immunoprecipitation. 
-#Windows of constant size (10 bp) are tiled across the genome at regular intervals (50 bp).
-if (pars$paired==TRUE){
-  pe.param <- readParam(max.frag=400, pe="both")
-  if ( length(pars$control.bams) > 1){
-    d1 <- windowCounts( c(bam.files, control.bams), bin=TRUE, width=10000, 
-                        ext=pars$frag.len, width=pars$win.width, param=pe.param)
-  } else { # no input bams
-    d1 <- windowCounts( bam.files, ext=pars$frag.len, width=pars$win.width, param=pe.param)
-  }
-} else { #single reads
-  if ( length(pars$control.bams) > 1){
-    d1 <- windowCounts( c(bam.files, control.bams), bin=TRUE, width=10000, 
-                        ext=pars$frag.len, width=pars$win.width, param=param)
-  } else { # no input bams
-    d1 <- windowCounts(bam.files, ext=pars$frag.len, width=pars$win.width, param=param)
-  }
-}
-if ( length(pars$control.bams) > 1){
-  chip    <- d1[,1:length(bam.files)]
-  control <- d1[,((length(bam.files) + 1):(length(bam.files) + length(control.bams)))]
-  filter.stat <- filterWindows(chip, control, type="control", prior.count=5,
-                               norm.fac=list(chip, control))
-  data <-filter.stat$filter > log2(3)
-} else {  # no input bams
-  abundances <- aveLogCPM(asDGEList(d1))
-  print("aveLogCPM abundances")
-  summary(abundances)
-  keep.simple <- abundances > aveLogCPM(5, lib.size=mean(d1$totals))
-  data <- d1[keep.simple, ]
-  summary(keep.simple)
-}
-# here implement the blacklist filter??
-
-# In edgeR, the log-transformed overall NB mean is referred to as the average abundance.
-# This is computed with the aveLogCPM function, as shown below for each region
-
-data$totals
-
-#max.delay <- 500
-dedup.on <- readParam(dedup=TRUE, minq=pars$min.quality)
-#x <- correlateReads(bam.files, $pars.max.delay, param=dedup.on)
-#plot(0:$pars.max.delay, x, type="l", ylab="CCF", xlab="Delay (bp)")
-
-normfacs <- normalize(data)
-normfacs
-y <- asDGEList(data, norm.factors=normfacs)
-cat("nrow(data: ") 
-nrow(data)
-grouping <- factor(samples)
-design <- model.matrix(~0 + grouping)
-colnames(design) <- levels(grouping)
-y <- asDGEList(data, norm.factors=normfacs)
-y <- estimateDisp(y, design)
-# biocLite("statmod")
-require(statmod)
-#install.packages("dplyr")
-library(dplyr)
-#install.packages("gridGraphics")
-#library(gridGraphics)
-fit <- glmQLFit(y, design, robust=TRUE)
-#contrast <- makeContrasts(es - tn, levels=design)
-cstring <- paste0(contrasts, collapse=' - ')
-contrast <- makeContrasts(cstring, levels=design)
-
-#QL  F-test  [Lund  et  al., 2012]
-results <- glmQLFTest(fit, contrast=contrast)
-
-merged <- mergeWindows(rowRanges(data), tol=pars$tol, max.width=pars$bin.win)
-
-# We demand replicates!
-#norep.fit <- glmFit(y, design, dispersion=0.05)
-#norep.results <- glmLRT(norep.fit, contrast=contrast)
-
-#bin.adjc <- cpm(asDGEList(binned.2), log=TRUE)
-#plotMDS(bin.adjc, labels=grouping)
-#plotBCV(y)
-#plotQLDisp(fit)
-
-clustered <- mergeWindows(rowRanges(data), tol=1000)
-clustered$region
-cat("entries in clustered: ")
-length(unique(clustered$id))
-
-# first method: Simes method
-# to  cluster  adjacent  windows  into  regions. A combined p-value can then be computed 
-# for each cluster, based on the p-values of the constituent windows [Simes, 1986]. 
-# This tests the joint null hypothesis for each cluster, i.e., that
-# no enrichment is observed across any sites within the corresponding region.  
-# The combined p-values are then adjusted using the BH method to control the region-level FDR.
-
-tabcom <- combineTests(clustered$id, results$table)
-print("Simes method")
-cat("entries in tabcom: ")
-length(tabcom$nWindows)
-head(tabcom)
-#is.sig.enrich <- select(tabcom, logFC.up > logFC.down & FDR<= pars$FDR)
-#cat("Significantly enriched regions: ", summary(is.sig.enrich))
-#is.sig.depleted <- select(tabcom, logFC.up < logFC.down & FDR<= pars$FDR)
-#cat("Significantly depleted regions: ", summary(is.sig.depleted))
-#summary(is.sig.depleted)
-
-tabcom$chr   <- seqnames(clustered$region)[as.numeric(row.names(tabcom))]
-tabcom$start <- start(clustered$region)[as.numeric(row.names(tabcom))]
-tabcom$stop  <- end(clustered$region)[as.numeric(row.names(tabcom))]
-#tabcom$start <- start(rowRanges(data))[tabcom$best]
-#tabcom$stop  <- end(rowRanges(data))[tabcom$best]
-tabCombyPadj <- tabcom[with(tabcom, order(FDR)), ] 
-cat("outfileSimes: ", outfileSimes,"\n")
-write.table(tabCombyPadj, file=outfileSimes, row.names=FALSE, quote=FALSE, sep="\t")
-
-# Alternative to Simes: getBestTest
-# choose a single window to represent each cluster/region.
-# For example, the window with the highest average abundance in each cluster can be used.
-# This is sensible for analyses involving sharp binding events, where each cluster is expected
-# to be small and contain no more than one binding site. Thus, a single window 
-# (and p-value) can reasonably be used as a representative of the entire region. 
-# The BH method can then be applied to the corresponding p-values 
-# of the representative windows from all clusters.
-
-clustered2 <- mergeWindows(rowRanges(data), tol=100, max.width=5000)
-tab.best <- getBestTest(clustered$id, results$table)
-
-tab.best$chr   <- seqnames(rowRanges(data))[tab.best$best]
-tab.best$start <- start(rowRanges(data))[tab.best$best]
-tab.best$stop  <- end(rowRanges(data))[tab.best$best]
-
-resultsbypadj <- tab.best[with(tab.best, order(FDR)), ] 
-cat("outfileBestTest: ", outfileBestTest, "\n")
-cat("entries in resultsbypadj: ")
-length(resultsbypadj$best)
-write.table(resultsbypadj, file=outfileBestTest, row.names=FALSE, quote=FALSE, sep="\t")
-
-quit() 

chipathlon/jobs/scripts/ccat_format_bed.pl

-#!/usr/bin/perl -w
-
-=NAME
-
-=VERSION
-
-=head1 SYNOPSYS
-From CCAT output format generates a decent, sorted BED file with no spaces
-Author: Istvan (Steve) Ladunga, University of Nebraska-Lincoln, sladunga@unl.edu
-=cut
-
-my $usage = << "EOF";
-
-Usage: $0  
-	-c input CCAT result file (significant.peak)
-	-b output BEDfile
-
-EOF
-
-use lib qw ( /home/ladunga/sladunga/bin/ /home/ladunga/sladunga/LIB/ /home/ladunga/perllib/ );
-use NoStatUtils;
-use strict;
-use Carp;
-use Getopt::Long;
-
-my %par = ( 
-		  ); 
-&GetOptions("c=s" => \$par{infile},
-	    "b=s" => \$par{outfile}); 
-
-
-($par{infile} && $par{outfile}) or die $usage;
-
-&go (\%par );
-
-print STDERR "$0 done\n";
-
-######################################################################
-
-sub go {
-    my ( $par ) = @_;
-    my $n = 0;
-    open (IN, "<$par->{infile}")  or die "Cannot open infile $par->{infile} $!\n";
-    my $tmpFile = '/tmp/ccatFormat2Bed.'.$$;
-    open (OF, ">$tmpFile") or die "Cannot open outfile $tmpFile $!\n";
-
-    while(<IN>){
-	chomp;
-	next if /^\#/;
-	next unless /\w/;
-#chr1    16523865        16522790        16526550        184     14      73.063558       0.001000
-	s/ +//g; # get rid of silly spaces
-	my @w = split;
-	my $name = 'ccat_'.$n;
-	my $start = ( $w[1] < $w[2] ) ? $w[1] : $w[2];
-	my $end = ( $w[1] < $w[2] ) ? $w[2] : $w[1];
-	my $s = join("\t", ($w[0], $start, $end, $name, $w[4], '.', $w[6], $w[7], 0.001 )); #, '.', $w[6]));
-	print OF "$s\n";
-	$n++;
-    }
-    close (IN);
-    close (OF);
-    `sort -k1,1V -k2,2n -k3,3n $tmpFile > $par->{outfile}`;
-}
-
-###################################################################
-

chipathlon/jobs/scripts/csaw_rscript.R

-library(argparse)
-
-parser <- ArgumentParser(description = "CSAW wrapper R script.")
-parser$add_argument("--workdir", dest="workdir", required=TRUE, help="Working directory.")
-parser$add_argument("--frag_len", dest="frag_len", default=20, help="Fragment Length.")
-parser$add_argument("--window_width", dest="window_width", default=20, help="Default window width.")
-parser$add_argument("--exp_bams", dest="exp_bams", nargs="+", required=TRUE, help="List of experiment bam files to use.")
-parser$add_argument("--exp_dir", dest="exp_dir", required=TRUE, help="Path to experiment directory.")
-parser$add_argument("--control_bams", dest="control_bams", nargs="+", required=TRUE, help="List of control bam files to use.")
-parser$add_argument("--control_dir", dest="control_dir", required=TRUE, help="List of control dirs to use.")
-parser$add_argument("--organism", dest="organism", required=TRUE, help="Organism name.")
-parser$add_argument("--tf", dest="tf", required=TRUE, help="Transcription factor.")
-parser$add_argument("--cond1", dest="cond1", required=TRUE, help="First condition.")
-parser$add_argument("--cond2", dest="cond2", required=TRUE, help="Second condition.")
-parser$add_argument("--samples", dest="samples", required=TRUE, nargs="+", help="?")
-parser$add_argument("--contrast", dest="contrast", required=TRUE, nargs="+", help="?")
-parser$add_argument("--id", dest="id", required=TRUE, help="?")
-parser$add_argument("--fdr", dest="fdr", default=0.05, help="False Discovery Rate.")
-parser$add_argument("--min_q", dest="min_q", default=30, help="Minimum quality score.")
-parser$add_argument("--paired", dest="paired", default=FALSE, action="store_true", help="Paired end reads.")
-parser$add_argument("--spacing", dest="spacing", default=50, help="?")
-parser$add_argument("--tol", dest="tol", default=100, help="?")
-args <- parser$parse_args()
-
-# partly based on https://www.bioconductor.org/help/course-materials/2015/BioC2015/csaw_lab.html
-# an example call:
-# where experiments came from GSE25532:
-# A.  K.  Tiwari,  M.  B.  Stadler,  C.  Wirbelauer,  R.  Paro,  D.  Schubeler,  and  C.  Beisel.
-# A chromatin-modifying function of JNK during stem cell dfferentiation.
-# Nat. Genet., 44(1): 94-100, Jan 2012
-
-#yaml.load_file( foo.yml )
-
-outfileStem <- paste0(c(args$analysisID, args$tf, args$cond1.cell, args$cond2.cell, args$orgn), collapse="_")
-outfileSimes<-paste0(c(outfileStem,'Simes.txt'), collapse="_")
-outfileBestTest<-paste0(c(outfileStem,'bestTest.txt'), collapse="_")
-cat( "Simes outfile: ", outfileSimes, " bestTestoutfile: ", outfileBestTest, "\n" )
-
-source("https://bioconductor.org/biocLite.R")
-setwd(args$workdir)
-
-bam.files <- file.path(args$exper.dir, args$exper.bams)
-cat("bam.files:\n")
-bam.files
-
-if ( length(args$control.bams) > 1){
-  control.bams <- file.path(args$control.dir, args$control.bams)
-  cat("Control (input) bam(s): ", control.bams, "\n" )
-}
-samples <- args$samples
-cat("Samples: ", samples, "\n" )
-contrasts<-args$contrast
-cat("Contrasts: ", contrasts, "\n" )
-# the blacklisted genomic regions
-library(GenomicRanges)
-if ( length(args$blacklist.regions) > 1){
-  blacklist.regions <- args$blacklist.regions
-} else {
-  if ( args$orgn == 'human'){
-
-  } else {
-    if ( args$orgn == 'mouse'){
-
-    } else {
-      cat("Organism: ", args$orgn, "not implemented yet, only human and mouse\n")
-      quit()
-    }
-  }
-}
-
-library(csaw)
-library(DESeq2)
-require(edgeR)
-param <- readParam(minq=args$min.quality)
-#Reads are directionally extended to the average fragment length,
-#to represent the original fragments that were present during immunoprecipitation.
-#Windows of constant size (10 bp) are tiled across the genome at regular intervals (50 bp).
-if (args$paired==TRUE){
-  pe.param <- readParam(max.frag=400, pe="both")
-  if ( length(args$control.bams) > 1){
-    d1 <- windowCounts( c(bam.files, control.bams), bin=TRUE, width=10000,
-                        ext=args$frag.len, width=args$win.width, param=pe.param)
-  } else { # no input bams
-    d1 <- windowCounts( bam.files, ext=args$frag.len, width=args$win.width, param=pe.param)
-  }
-} else { #single reads
-  if ( length(args$control.bams) > 1){
-    d1 <- windowCounts( c(bam.files, control.bams), bin=TRUE, width=10000,
-                        ext=args$frag.len, width=args$win.width, param=param)
-  } else { # no input bams
-    d1 <- windowCounts(bam.files, ext=args$frag.len, width=args$win.width, param=param)
-  }
-}
-