diff --git a/public/biopet-framework/src/main/resources/log4j.properties b/public/biopet-framework/src/main/resources/log4j.properties deleted file mode 100644 index 82aef1c853b2047cc3376ccfadd7f0465a990695..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/log4j.properties +++ /dev/null @@ -1,26 +0,0 @@ -# -# Biopet is built on top of GATK Queue for building bioinformatic -# pipelines. It is mainly intended to support LUMC SHARK cluster which is running -# SGE. But other types of HPC that are supported by GATK Queue (such as PBS) -# should also be able to execute Biopet tools and pipelines. -# -# Copyright 2014 Sequencing Analysis Support Core - Leiden University Medical Center -# -# Contact us at: sasc@lumc.nl -# -# A dual licensing mode is applied. The source code within this project that are -# not part of GATK Queue is freely available for non-commercial use under an AGPL -# license; For commercial users or users who do not want to follow the AGPL -# license, please contact us to obtain a separate license. -# - -# Set root logger level to DEBUG and its only appender to A1. -log4j.rootLogger=INFO, A1 - -# A1 is set to be a ConsoleAppender. -log4j.appender.A1=org.apache.log4j.ConsoleAppender -log4j.appender.A1.Target=System.err - -# A1 uses PatternLayout. -log4j.appender.A1.layout=org.apache.log4j.PatternLayout -log4j.appender.A1.layout.ConversionPattern=%-5p [%d] [%C{1}] - %m%n \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/License.txt b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/License.txt deleted file mode 100644 index b8262cb45d8b3642d018d84cacde9454062f54f8..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/License.txt +++ /dev/null @@ -1,13 +0,0 @@ -Biopet is built on top of GATK Queue for building bioinformatic -pipelines. It is mainly intended to support LUMC SHARK cluster which is running -SGE. But other types of HPC that are supported by GATK Queue (such as PBS) -should also be able to execute Biopet tools and pipelines. - -Copyright 2014 Sequencing Analysis Support Core - Leiden University Medical Center - -Contact us at: sasc@lumc.nl - -A dual licensing mode is applied. The source code within this project that are -not part of GATK Queue is freely available for non-commercial use under an AGPL -license; For commercial users or users who do not want to follow the AGPL -license, please contact us to obtain a separate license. \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/executables.ssp b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/executables.ssp deleted file mode 100644 index 0dcb32c20659700440cef5f214a6d0f7e6e5a0c4..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/executables.ssp +++ /dev/null @@ -1,33 +0,0 @@ -#import(nl.lumc.sasc.biopet.utils.summary.Summary) -#import(nl.lumc.sasc.biopet.core.report.ReportPage) -<%@ var summary: Summary %> -<%@ var rootPath: String %> -<%@ var sampleId: Option[String] = None %> -<%@ var libId: Option[String] = None %> -<%@ var pipeline: String = summary.getValue("meta", "pipeline_name").getOrElse("").toString %> -#{ - val executables = summary.getValue(sampleId, libId, pipeline, "executables").getOrElse(Map()).asInstanceOf[Map[String, Map[String, Any]]] -}# - -<table class="table"> - <thead> - <tr> - <th>Name</th> - <th>Version</th> - </tr> - </thead> - <tbody> - #for (name <- executables.keySet.toList.sorted) - <tr> - <td>${name}</td> - #{ - val version = executables(name).get("version") match { - case Some(x) if x != None => x.toString - case _ => "N/A" - } - }# - <td>${version}</td> - </tr> - #end - </tbody> -</table> \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/ext/css/bootstrap-theme.min.css b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/ext/css/bootstrap-theme.min.css deleted file mode 100644 index cefa3d1ae367429a366230ca2c4c995616bb0790..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/ext/css/bootstrap-theme.min.css +++ /dev/null @@ -1,5 +0,0 @@ -/*! - * Bootstrap v3.3.4 (http://getbootstrap.com) - * Copyright 2011-2015 Twitter, Inc. - * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE) - */.btn-danger,.btn-default,.btn-info,.btn-primary,.btn-success,.btn-warning{text-shadow:0 -1px 0 rgba(0,0,0,.2);-webkit-box-shadow:inset 0 1px 0 rgba(255,255,255,.15),0 1px 1px rgba(0,0,0,.075);box-shadow:inset 0 1px 0 rgba(255,255,255,.15),0 1px 1px rgba(0,0,0,.075)}.btn-danger.active,.btn-danger:active,.btn-default.active,.btn-default:active,.btn-info.active,.btn-info:active,.btn-primary.active,.btn-primary:active,.btn-success.active,.btn-success:active,.btn-warning.active,.btn-warning:active{-webkit-box-shadow:inset 0 3px 5px rgba(0,0,0,.125);box-shadow:inset 0 3px 5px rgba(0,0,0,.125)}.btn-danger .badge,.btn-default .badge,.btn-info .badge,.btn-primary .badge,.btn-success 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a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/librariesList.ssp +++ /dev/null @@ -1,13 +0,0 @@ -#import(nl.lumc.sasc.biopet.utils.summary.Summary) -#import(nl.lumc.sasc.biopet.core.report.ReportPage) -<%@ var summary: Summary %> -<%@ var rootPath: String %> -<%@ var sampleId: Option[String] = None %> -<table class="table"> -<thead><tr><th>Libraries</th></tr></thead> -<tbody> -#for (lib <- summary.libraries(sampleId.get)) - <tr><td><a href="${rootPath}Samples/${sampleId}/Libraries/${lib}/index.html">${lib}</a></td></tr> -#end -</tbody> -</table> \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/main.ssp b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/main.ssp deleted file mode 100644 index b706ac45804afd61411115fbd47ca93bfbaa1fb9..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/main.ssp +++ /dev/null @@ -1,158 +0,0 @@ -#import(nl.lumc.sasc.biopet.utils.summary.Summary) -#import(nl.lumc.sasc.biopet.core.report.ReportPage) -<%@ var summary: Summary %> -<%@ var indexPage: ReportPage %> -<%@ var reportName: String %> -<%@ var page: ReportPage %> -<%@ var path: List[String] %> -<%@ var args: Map[String, Any] %> -<%@ var rootPath: String %> -#{ - def createMenu(page: ReportPage, path: List[String] = Nil, first: Boolean = true): String = { - val buffer: StringBuffer = new StringBuffer() - - if (page.subPages.nonEmpty){ - buffer.append("<ul class=\"dropdown-menu\">") - } - - for (subPage <- page.subPages) { - val href: String = { - if (path.isEmpty) rootPath + subPage._1 + "/index.html" - else rootPath + path.mkString("","/","/") + subPage._1 + "/index.html" - } - - buffer.append("<li") - if(subPage._2.subPages.nonEmpty) buffer.append(" class=\"dropdown-submenu\"") - buffer.append("><a href=\"" + href + "\"") - if (first) buffer.append(" tabindex=\"-1\"") - buffer.append(">" + subPage._1 + "</a>") - buffer.append(createMenu(subPage._2, path ::: subPage._1 :: Nil, first = false)) - buffer.append("</li>") - } - if(page.subPages.nonEmpty) { - buffer.append("</ul>\n") - } - buffer.toString - } - - def getSubPage(path:List[String]): ReportPage = { - path.foldLeft(indexPage)((c, p) => { - val foundPages = c.subPages.filter(_._1 == p) - require(foundPages.size == 1, "Name of page not found or duplicate is found, page:: " + p + " in path: " + path) - foundPages.head._2 - }) - } -}# -<!DOCTYPE html> -<html> - <head> - <title>${reportName}</title> - - <!-- Bootstrap core JavaScript - ================================================== --> - <!-- Placed at the end of the document so the pages load faster --> - <script src="${rootPath}ext/js/jquery.min.js"></script> - - <!-- Latest compiled and minified CSS --> - <link rel="stylesheet" href="${rootPath}ext/css/bootstrap.min.css"> - - <!-- Optional theme --> - <link rel="stylesheet" href="${rootPath}ext/css/bootstrap-theme.min.css"> - - <!-- Latest compiled and minified JavaScript --> - <script src="${rootPath}ext/js/bootstrap.min.js"></script> - - <link rel="stylesheet" type="text/css" href="${rootPath}ext/css/bootstrap_dashboard.css"> - <link rel="stylesheet" type="text/css" href="${rootPath}ext/css/sortable-theme-bootstrap.css"> - - <!-- sortable tables //--> - <script src="${rootPath}ext/js/sortable.min.js"></script> - <script language="JavaScript"> - <!-- - $(document).ready(function() { - Sortable.init() - - $('body').scrollspy({ - target: '.bs-sidebar', - }); - }); - - //--> - </script> - </head> -<body> - -<nav class="navbar navbar-inverse navbar-fixed-top"> -<div class="container"> - <div class="navbar-header"> - <button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-ex1-collapse"> - <span class="sr-only">Toggle navigation</span> - <span class="icon-bar"></span> - <span class="icon-bar"></span> - <span class="icon-bar"></span> - </button> - - <ul class="nav navbar-nav"> - <li class="root #if (path.isEmpty) active #end"> - <a class="navbar-brand" href="${rootPath}index.html">${reportName} - #if (indexPage.subPages.nonEmpty) <b class="caret"></b> #end - </a> - ${unescape(createMenu(indexPage))} - </li> - </ul> - </div> - - <div class="collapse navbar-collapse navbar-ex1-collapse"> - <ul class="nav navbar-nav"> - <!-- ${path.size} //--> - <!-- ${path} //--> - #for (t <- 1 to path.size) - #if(t == 0) - <li class="root"> - <a href="${rootPath}index.html">Home - #if (indexPage.subPages.nonEmpty) <b class="caret"></b> #end - </a> - ${unescape(createMenu(indexPage))} - </li> - #else - <li class="root #if (t == path.size) active #end"> - <a href="${rootPath}${path.slice(0,t).mkString("", "/", "/")}index.html">${path( t - 1 )} - #if (getSubPage(path.slice(0, t)).subPages.nonEmpty) <b class="caret"></b> #end - </a> - ${unescape(createMenu(getSubPage(path.slice(0, t)), path.slice(0, t)))} - </li> - #end - #end - - </ul> - </div> - <!--/.nav-collapse --> -</div> -</nav> - -<div class="container-fluid"> -<div class="row"> - <div id="side-nav" class="col-sm-3 col-md-2 sidebar"> - <ul class="nav nav-sidebar nav-list bs-sidebar"> - #for ((name, url) <- page.sections) - <li><a href="#${name}">${name}</a></li> - #end - </ul> - </div> - <div class="col-sm-9 col-sm-offset-3 col-md-10 col-md-offset-2 main content"> - #for ((name, section) <- page.sections) - <div id="${name}" class="panel panel-primary"> - <div class="panel-heading"> - <h3 class="panel-title" id="panel-title"> - ${name} - </h3> - </div> - ${unescape(section.render(args))} - </div> - #end - </div> -</div> -</div> - -</body> -</html> \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/reference.ssp b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/reference.ssp deleted file mode 100644 index b12db503c8217bacf150c52a0e8c32b9949a4f6b..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/reference.ssp +++ /dev/null @@ -1,31 +0,0 @@ -#import(nl.lumc.sasc.biopet.utils.summary.Summary) -#import(nl.lumc.sasc.biopet.core.report.ReportPage) -<%@ var summary: Summary %> -<%@ var rootPath: String %> -<%@ var pipeline: String %> - -#{ - val contigs = summary.getValue(pipeline, "settings", "reference", "contigs").get.asInstanceOf[Map[String, Map[String, Any]]] -}# - -<table class="table"> - <tbody> - <tr><th>Species</th><td>${summary.getValue(pipeline, "settings", "reference", "species")}</td></tr> - <tr><th>Name</th><td>${summary.getValue(pipeline, "settings", "reference", "name")}</td></tr> - <tr><th>File</th><td>${summary.getValue(pipeline, "files", "pipeline", "referenceFasta", "path")}</td></tr> - <tr><th>MD5</th><td>${summary.getValue(pipeline, "files", "pipeline", "referenceFasta", "md5")}</td></tr> - </tbody> -</table> - -<br/> - -<table class="table sortable-theme-bootstrap" data-sortable> - <thead> - <tr><th>Contig Name</th><th data-sorted="true" data-sorted-direction="descending">Length</th><th>MD5</th></tr> - </thead> - <tbody> - #for (c <- contigs.toList.sortBy(_._2("length").asInstanceOf[Long]).reverse) - <tr><th>${c._1}</th><td>${c._2.get("length")}</td><td>${c._2.get("md5")}</td></tr> - #end - </tbody> -</table> \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/samplesList.ssp b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/samplesList.ssp deleted file mode 100644 index 20f6945618a17055380a9289d082c1655939f872..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/core/report/samplesList.ssp +++ /dev/null @@ -1,12 +0,0 @@ -#import(nl.lumc.sasc.biopet.utils.summary.Summary) -#import(nl.lumc.sasc.biopet.core.report.ReportPage) -<%@ var summary: Summary %> -<%@ var rootPath: String %> -<table class="table sortable-theme-bootstrap" data-sortable> - <thead><tr><th data-sorted="true" data-sorted-direction="ascending">Sample</th></tr></thead> - <tbody> - #for (sample <- summary.samples) - <tr><td><a href="${rootPath}Samples/${sample}/index.html">${sample}</a></td></tr> - #end - </tbody> -</table> \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/extensions/breakdancer/breakdancer2vcf.py b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/extensions/breakdancer/breakdancer2vcf.py deleted file mode 100644 index 8dd93a0e8c836c43e1424e98903dd1b239d5e12d..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/extensions/breakdancer/breakdancer2vcf.py +++ /dev/null @@ -1,192 +0,0 @@ -#!/usr/bin/env python -# -# Biopet is built on top of GATK Queue for building bioinformatic -# pipelines. It is mainly intended to support LUMC SHARK cluster which is running -# SGE. But other types of HPC that are supported by GATK Queue (such as PBS) -# should also be able to execute Biopet tools and pipelines. -# -# Copyright 2014 Sequencing Analysis Support Core - Leiden University Medical Center -# -# Contact us at: sasc@lumc.nl -# -# A dual licensing mode is applied. The source code within this project that are -# not part of GATK Queue is freely available for non-commercial use under an AGPL -# license; For commercial users or users who do not want to follow the AGPL -# license, please contact us to obtain a separate license. -# - -__copyright__ = """ -Copyright (C) 2013 - Tim te Beek -Copyright (C) 2013 - Wai Yi Leung -Copyright (C) 2013 AllBio (see AUTHORS file) -""" - -__desc__ = """Convert breakdancer output to VCF v4.2 .file format.""" -__created__ = "Mar 18, 2013" -__author__ = "tbeek,wyleung" - -import argparse -import csv -import datetime - - -def main(tsvfile, vcffile): - ''' - :param tsvfile: filename of input file.tsv - :type tsvfile: string - :param vcffile: filename of output file.vcf - :type vcffile: string - ''' - with open(tsvfile) as reader: - # Parse file - dictreader = _parse_tsvfile(reader) - - # Write out file - _format_vcffile(dictreader, vcffile) - -def _parse_tsvfile(readable): - ''' - Read readable using csv.Sniffer and csv.DictReader - :param readable: open file.tsv handle to read with csv.DictReader - :type readable: file - ''' - prev, curr = 0, 0 - while True: - line = readable.readline() - if not line.startswith('#'): - # lets start from prev # line, without the hash sign - readable.seek(prev + 1) - break - else: - prev = curr - curr = readable.tell() - - # Determine dialect - curr = readable.tell() - #dialect = csv.Sniffer().sniff(readable.read(3000)) - dialect = 'excel-tab' - readable.seek(curr) - - # Read file - dictreader = csv.DictReader(readable, dialect=dialect) - return dictreader - - -_tsv_fields = ('Chr1', 'Pos1', 'Orientation1', - 'Chr2', 'Pos2', 'Orientation2', - 'Type', 'Size', 'Score', - 'num_Reads', 'num_Reads_lib', - 'ERR031544.sort.bam') -# 'Chr1': '1', -# 'Pos1': '269907', -# 'Orientation1': '39+39-', -# 'Chr2': '1', -# 'Pos2': '270919', -# 'Orientation2': '39+39-', -# 'Type': 'DEL', -# 'Size': '99', -# 'Score': '99', -# 'num_Reads': '38', -# 'num_Reads_lib': '/home/allbio/ERR031544.sort.bam|38', -# 'ERR031544.sort.bam': 'NA' - - - -_vcf_fields = ('CHROM', 'POS', 'ID', 'REF', 'ALT', 'QUAL', 'FILTER', 'INFO', 'FORMAT', 'default') - -TS_NOW = datetime.datetime.now() - -VCF_HEADER = """##fileformat=VCFv4.1 -##fileDate={filedate} -##source=breakdancer-max -##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data"> -##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth"> -##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency"> -##INFO=<ID=IMPRECISE,Number=0,Type=Flag,Description="Imprecise structural variation"> -##INFO=<ID=NOVEL,Number=0,Type=Flag,Description="Indicates a novel structural variation"> -##INFO=<ID=SVEND,Number=1,Type=Integer,Description="End position of the variant described in this record"> -##INFO=<ID=END,Number=1,Type=Integer,Description="End position of the variant described in this record"> -##INFO=<ID=SVTYPE,Number=1,Type=String,Description="Type of structural variant"> -##INFO=<ID=SVLEN,Number=.,Type=Integer,Description="Difference in length between REF and ALT alleles"> -##INFO=<ID=CIPOS,Number=2,Type=Integer,Description="Confidence interval around POS for imprecise variants"> -##INFO=<ID=CIEND,Number=2,Type=Integer,Description="Confidence interval around END for imprecise variants"> -##INFO=<ID=HOMLEN,Number=.,Type=Integer,Description="Length of base pair identical micro-homology at event breakpoints"> -##INFO=<ID=HOMSEQ,Number=.,Type=String,Description="Sequence of base pair identical micro-homology at event breakpoints"> -##INFO=<ID=BKPTID,Number=.,Type=String,Description="ID of the assembled alternate allele in the assembly file"> -##INFO=<ID=MEINFO,Number=4,Type=String,Description="Mobile element info of the form NAME,START,END,POLARITY"> -##INFO=<ID=METRANS,Number=4,Type=String,Description="Mobile element transduction info of the form CHR,START,END,POLARITY"> -##INFO=<ID=DGVID,Number=1,Type=String,Description="ID of this element in Database of Genomic Variation"> -##INFO=<ID=DBVARID,Number=1,Type=String,Description="ID of this element in DBVAR"> -##INFO=<ID=DBRIPID,Number=1,Type=String,Description="ID of this element in DBRIP"> -##INFO=<ID=MATEID,Number=.,Type=String,Description="ID of mate breakends"> -##INFO=<ID=PARID,Number=1,Type=String,Description="ID of partner breakend"> -##INFO=<ID=EVENT,Number=1,Type=String,Description="ID of event associated to breakend"> -##INFO=<ID=CILEN,Number=2,Type=Integer,Description="Confidence interval around the inserted material between breakends"> -##INFO=<ID=DP,Number=1,Type=Integer,Description="Read Depth of segment containing breakend"> -##INFO=<ID=DPADJ,Number=.,Type=Integer,Description="Read Depth of adjacency"> -##INFO=<ID=CN,Number=1,Type=Integer,Description="Copy number of segment containing breakend"> -##INFO=<ID=CNADJ,Number=.,Type=Integer,Description="Copy number of adjacency"> -##INFO=<ID=CICN,Number=2,Type=Integer,Description="Confidence interval around copy number for the segment"> -##INFO=<ID=CICNADJ,Number=.,Type=Integer,Description="Confidence interval around copy number for the adjacency"> -##FORMAT=<ID=CN,Number=1,Type=Integer,Description="Copy number genotype for imprecise events"> -##FORMAT=<ID=CNQ,Number=1,Type=Float,Description="Copy number genotype quality for imprecise events"> -##FORMAT=<ID=CNL,Number=.,Type=Float,Description="Copy number genotype likelihood for imprecise events"> -##FORMAT=<ID=NQ,Number=1,Type=Integer,Description="Phred style probability score that the variant is novel"> -##FORMAT=<ID=HAP,Number=1,Type=Integer,Description="Unique haplotype identifier"> -##FORMAT=<ID=AHAP,Number=1,Type=Integer,Description="Unique identifier of ancestral haplotype"> -##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype"> -##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality"> -##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">""".format( filedate=TS_NOW.strftime( "%Y%m%d" ) ) - -def _format_vcffile(dictreader, vcffile): - ''' - Create a pseudo .vcf file based on values read from DictReader instance. - :param dictreader: DictReader instance to read data from - :type dictreader: csv.DictRedaer - :param vcffile: output file.vcf filename - :type vcffile: string - ''' - FORMAT = "GT:DP" - with open(vcffile, mode='w') as writer: - writer.write('{header}\n#{columns}\n'.format(header=VCF_HEADER, columns='\t'.join(_vcf_fields))) - output_vcf = [] - for line in dictreader: - CHROM = line['Chr1'] - # TODO Figure out whether we have zero or one based positioning - POS = int(line['Pos1']) - ALT = '.' - SVEND = int(line['Pos2']) - - INFO = 'PROGRAM=breakdancer;SVTYPE={}'.format(line['Type']) - - if line['Type'] not in ['CTX']: - INFO += ';SVLEN={}'.format(int(line['Size'])) - INFO += ";SVEND={}".format(SVEND) - INFO += ";END={}".format(SVEND) - - # write alternate ALT field for Intrachromosomal translocations - if line['Type'] in ['CTX']: - ALT = "N[{}:{}[".format(line['Chr2'], line['Pos2']) - - - - SAMPLEINFO = "{}:{}".format( '1/.', line['num_Reads'] ) - # Create record - output_vcf.append([CHROM, POS, '.', '.', ALT, '.', 'PASS', INFO, FORMAT, SAMPLEINFO]) - - # Sort all results - output_vcf.sort() - output = "\n".join(["\t".join(map(str,vcf_row)) for vcf_row in output_vcf]) - # Write record - writer.write(output) - - -if __name__ == '__main__': - parser = argparse.ArgumentParser() - parser.add_argument('-i', '--breakdancertsv', dest='breakdancertsv', type=str, - help='Breakdancer TSV outputfile') - parser.add_argument('-o', '--outputvcf', dest='outputvcf', type=str, - help='Output vcf to') - - args = parser.parse_args() - main(args.breakdancertsv, args.outputvcf) diff --git a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/scripts/bedtools_cov_stats.py b/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/scripts/bedtools_cov_stats.py deleted file mode 100755 index 71c60d37a8daa5a52e80a777d21d1d413f3d9936..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/nl/lumc/sasc/biopet/scripts/bedtools_cov_stats.py +++ /dev/null @@ -1,321 +0,0 @@ -#!/usr/bin/env python2.7 -# -# Biopet is built on top of GATK Queue for building bioinformatic -# pipelines. It is mainly intended to support LUMC SHARK cluster which is running -# SGE. But other types of HPC that are supported by GATK Queue (such as PBS) -# should also be able to execute Biopet tools and pipelines. -# -# Copyright 2014 Sequencing Analysis Support Core - Leiden University Medical Center -# -# Contact us at: sasc@lumc.nl -# -# A dual licensing mode is applied. The source code within this project that are -# not part of GATK Queue is freely available for non-commercial use under an AGPL -# license; For commercial users or users who do not want to follow the AGPL -# license, please contact us to obtain a separate license. -# - - -""" -Plot output of coverageBed / "bedtools coverage" when run with the -d flag. - - -This script plots a bar graph showing how many times a base covered X times -are found. An additional box plot is also plotted to show the general trend -of the coverage. - -By default, the bar graph only shows the data up to the 98th percentile. -Counts for bases that are not covered (0x coverage) are shown in lighter -shade. The median, quartile, and whiskers values shown in the boxplot are -still computed from the complete data set (0x coverage included). - -Requirements: - * Python == 2.7.x - * Matplotlib >= 1.3.0 - * Numpy >= 1.8.0 - -Copyright (c) 2013 Wibowo Arindrarto <w.arindrarto@lumc.nl> -Copyright (c) 2013 LUMC Sequencing Analysis Support Core <sasc@lumc.nl> -MIT License <http://opensource.org/licenses/MIT> -""" - -RELEASE = False -__version_info__ = ('0', '1', ) -__version__ = '.'.join(__version_info__) -__version__ += '-dev' if not RELEASE else '' - - -import argparse -import collections -import itertools -import json -import locale -import os -import sys - -import matplotlib -matplotlib.use('Agg') -import matplotlib.gridspec as gs -import matplotlib.pyplot as plt -import matplotlib.ticker as tkr -import numpy as np - - -BLUE = '#2166AC' -RED = '#1A9850' -GREEN = '#D6604D' - -locale.setlocale(locale.LC_ALL, '') -group_digits = lambda x, pos: locale.format('%d', x, grouping=True) -major_formatter = tkr.FuncFormatter(group_digits) - - -def cachedproperty(func): - """Decorator for cached property loading.""" - attr_name = func.__name__ - @property - def cached(self): - if not hasattr(self, '_cache'): - setattr(self, '_cache', {}) - try: - return self._cache[attr_name] - except KeyError: - result = self._cache[attr_name] = func(self) - return result - return cached - - -class Coverage(object): - - """Class representing coverage metrics from a coverageBed -d output.""" - - def __init__(self, cvg_list, name='?'): - """ - - :param cvg_list: iterator yielding coverage per position - :type cvg_list: iterable - - """ - assert cvg_list - counter = collections.Counter() - total_bases, nonzero_bases = 0, 0 - for cvg in cvg_list: - counter[cvg] += 1 - total_bases += 1 - if cvg > 0: - nonzero_bases += 1 - - self._counter = counter - self.total_bases = total_bases - self.nonzero_bases = nonzero_bases - - def __iter__(self): - return self._counter.iteritems() - - def __repr__(self): - return "{0}(...)".format(self.__class__.__name__) - - @cachedproperty - def total(self): - """Total coverage.""" - return sum([cvg * count for cvg, count in self]) - - @cachedproperty - def horizontal(self): - """Horizontal coverage (0 - 1).""" - return float(self.nonzero_bases) / self.total_bases - - @cachedproperty - def mean(self): - """Average coverage.""" - return float(self.total) / self.total_bases - - @cachedproperty - def max(self): - """Maximum coverage.""" - return max(self._counter.keys()) - - @cachedproperty - def median(self): - """Median coverage.""" - return np.percentile(self.cov_counts, 50) - - @cachedproperty - def cov_counts(self): - """List of coverage for each base position (unsorted).""" - # get list of each base coverage - cov_counts = ([key] * value for key, value in self._counter.items()) - # and flatten the list - return [item for sublist in cov_counts for item in sublist] - - def at_least(self, n): - """Return the percentages of bases covered at least n times.""" - x = sum([count for cvg, count in self if cvg >= n]) - return float(x) / self.total_bases - - def get_quick_stats(self): - """Returns a dictionary containing quick coverage statistics.""" - return { - 'max': self.max, - 'median': self.median, - 'mean': self.mean, - 'horizontal': self.horizontal, - 'width': self.total_bases, - 'width_nonzero': self.nonzero_bases, - 'total': self.total, - 'frac_min_10x': self.at_least(10), - 'frac_min_20x': self.at_least(20), - 'frac_min_30x': self.at_least(30), - 'frac_min_40x': self.at_least(40), - 'frac_min_50x': self.at_least(50), - } - - def plot(self, min_cov_ok=7, percentile_show=98, title=None, out_img=None): - """Plots the coverage object. - - :param min_cov_ok: Minimum coverage value to show in the bar graph - (default: 7). - :type min_cov_ok: int - :param percentile_show: Maximum percentile to show in the bar graph - (default: 98). - :type percentile_show: int - :param title: Plot title - :type title: list of strings (one item per line) - :param out_img: Output image filename. - :type out_img: str - - """ - plt.figure(figsize=(8, 8)) - grids = gs.GridSpec(2, 1, height_ratios=[5, 1]) - - ax0 = plt.subplot(grids[0]) - - if title is None: - title = ['Coverage Plot'] - elif isinstance(title, basestring): - title = [title] - t = plt.title('\n'.join(title), fontsize=20) - t.set_y(1.05) - - x_data, y_data = [], [] - x_data_shade, y_data_shade = [], [] - for coverage, count in self: - if coverage >= min_cov_ok: - x_data.append(coverage) - y_data.append(count) - else: - x_data_shade.append(coverage) - y_data_shade.append(count) - - ax0.bar(x_data, y_data, width=1, linewidth=0, color=BLUE, align='center') - ax0.yaxis.set_major_formatter(major_formatter) - ax0.grid(True) - plt.ylabel('Counts') - ax0.text(0.5, 0.95, 'Mean: %.2fx Median: %.2fx ' - 'Horizontal: %.2f%%' % (self.mean, self.median, 100.0 * \ - self.horizontal), verticalalignment='center', - horizontalalignment='center', transform=ax0.transAxes, - bbox=dict(facecolor='wheat', alpha=0.5, boxstyle='round'), - size=12) - - ax1 = plt.subplot(grids[1], sharex=ax0) - ax1.axes.get_yaxis().set_visible(False) - bp = ax1.boxplot(self.cov_counts, vert=False, widths=0.6, sym='+') - for x in itertools.chain(bp['boxes'], bp['medians'], bp['whiskers'], - bp['caps']): - x.set(color=BLUE, linewidth=1.6) - for flier in bp['fliers']: - plt.setp(flier, color='GREEN', alpha=0.5) - - upper_limit = np.percentile(self.cov_counts, percentile_show) - if x_data: - space = (upper_limit - min(x_data)) / 40 - else: - space = 0 - # truncate plot if we're not displaying maximum value - if upper_limit != self.max: - ax1.set_xlim([min(self.cov_counts) - space - 0.5, upper_limit + 0.5]) - # otherwise, give some space - else: - ax1.set_xlim([min(self.cov_counts) - space - 0.5, upper_limit + - space + 0.5]) - - # plot shaded values - if x_data_shade: - ylim = ax0.get_ylim() - ax0.bar(x_data_shade, y_data_shade, width=1, linewidth=0, - color=BLUE, alpha=0.3, align='center') - ax0.set_ylim(ylim) - - plt.xlabel('Coverage') - grids.update(hspace=0.075) - - if out_img is not None: - plt.savefig(out_img, bbox_inches='tight') - - -if __name__ == '__main__': - - usage = __doc__.split('\n\n\n') - parser = argparse.ArgumentParser( - formatter_class=argparse.RawDescriptionHelpFormatter, - description=usage[0], epilog=usage[1]) - - parser.add_argument('input', type=str, help='Path to input file ' - '(coverageBed output) or \'-\' for stdin') - parser.add_argument('--plot', dest='plot', type=str, - help='Path to output PNG file') - parser.add_argument('--min-cov-show', dest='min_cov_ok', type=int, - default=6, help='Minimum coverage to show in bar graph') - parser.add_argument('--max-percentile-show', dest='max_pct_show', type=int, - default=98, help='Maximum percentile to show in bar graph') - parser.add_argument('--title', dest='title', type=str, - default='Coverage Plot', help='Plot title') - parser.add_argument('--subtitle', dest='subtitle', type=str, help='Plot subtitle') - - args = parser.parse_args() - - if args.input == '-': - instream = sys.stdin - else: - instream = open(args.input, 'r') - - title = [args.title] - if args.subtitle is None: - title.append("'" + args.input + "'") - else: - title.append(args.subtitle) - - coverages = {} - all_covs, cur_covs = [], [] - cur_chrom, prev_chrom = None, None - for line in (l.strip() for l in instream): - cols = line.split('\t') - cur_chrom = cols[0] - cvg = int(cols[-1]) - # coverage for all positions - all_covs.append(cvg) - # coverage per chromosome - if cur_chrom != prev_chrom: - if prev_chrom is not None: - coverages[prev_chrom] = cur_covs - cur_covs = [] - prev_chrom = cur_chrom - cur_covs.append(cvg) - # also append the last chromosome from the file - coverages[cur_chrom] = cur_covs - - coverages['_all'] = all_covs - - for cname, clist in coverages.items(): - coverages[cname] = Coverage(clist) - - if args.input != '-': - instream.close() - - if args.plot is not None: - coverages['_all'].plot(min_cov_ok=args.min_cov_ok, percentile_show=args.max_pct_show, - title=title, out_img=args.plot) - - stats = {'coverage': {k: v.get_quick_stats() for k, v in coverages.items()}} - json.dump(stats, sys.stdout, sort_keys=True, indent=4, separators=(',', ': ')) \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/org/broadinstitute/gatk/queue/util/queueJobReport.R b/public/biopet-framework/src/main/resources/org/broadinstitute/gatk/queue/util/queueJobReport.R deleted file mode 100644 index 5f53b340f803582c501beed6f86fbf2b11155d7b..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/org/broadinstitute/gatk/queue/util/queueJobReport.R +++ /dev/null @@ -1,243 +0,0 @@ -library(gsalib) -library(grid) -library(ggplot2) -library(gplots) -library(tools) -library(reshape) -library(plyr) - -# Modified version, loading `grid` manually. Ggplot2 doesn't load this - -# -# Standard command line switch. Can we loaded interactively for development -# or executed with RScript -# -args = commandArgs(TRUE) -onCMDLine = ! is.na(args[1]) -if ( onCMDLine ) { - inputFileName = args[1] - outputPDF = args[2] -} else { - inputFileName = "~/workspaces/scratch/SingleSample_VQSRwNewSOR.jobreport.txt" - #inputFileName = "/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/Q-25718@node1149.jobreport.txt" - #inputFileName = "/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/rodPerformanceGoals/history/report.082711.txt" - outputPDF = NA -} - -RUNTIME_UNITS = "(hours)" -ORIGINAL_UNITS_TO_RUNTIME_UNITS = 1/1000/60/60 - -# -# Helper function to aggregate all of the jobs in the report across all tables -# -allJobsFromReport <- function(report) { - names <- c("jobName", "startTime", "analysisName", "doneTime", "exechosts", "runtime") - sub <- lapply(report, function(table) table[,names]) - do.call("rbind", sub) -} - -# -# Creates segmentation plots of time (x) vs. job (y) with segments for the duration of the job -# -plotJobsGantt <- function(gatkReport, sortOverall, title, includeText) { - allJobs = allJobsFromReport(gatkReport) - if ( sortOverall ) { - allJobs = allJobs[order(allJobs$analysisName, allJobs$startTime, decreasing=T), ] - } else { - allJobs = allJobs[order(allJobs$startTime, decreasing=T), ] - } - allJobs$index = 1:nrow(allJobs) - minTime = min(allJobs$startTime) - allJobs$relStartTime = allJobs$startTime - minTime - allJobs$relDoneTime = allJobs$doneTime - minTime - allJobs$ganttName = paste(allJobs$jobName, "@", allJobs$exechosts) - maxRelTime = max(allJobs$relDoneTime) - p <- ggplot(data=allJobs, aes(x=relStartTime, y=index, color=analysisName)) - p <- p + theme_bw() - p <- p + geom_segment(aes(xend=relDoneTime, yend=index), size=1, arrow=arrow(length = unit(0.1, "cm"))) - if ( includeText ) - p <- p + geom_text(aes(x=relStartTime, label=ganttName, hjust=0, vjust=-1), size=2) - p <- p + xlim(0, maxRelTime * 1.3) - p <- p + xlab(paste("Start time, relative to first job", RUNTIME_UNITS)) - p <- p + ylab("Job number") - p <- p + ggtitle(title) - print(p) -} - -# -# Plots scheduling efficiency at job events -# -plotProgressByTime <- function(gatkReport) { - allJobs = allJobsFromReport(gatkReport) - nJobs = dim(allJobs)[1] - allJobs = allJobs[order(allJobs$startTime, decreasing=F),] - allJobs$index = 1:nrow(allJobs) - - minTime = min(allJobs$startTime) - allJobs$relStartTime = allJobs$startTime - minTime - allJobs$relDoneTime = allJobs$doneTime - minTime - - times = sort(c(allJobs$relStartTime, allJobs$relDoneTime)) - - countJobs <- function(p) { - s = allJobs$relStartTime - e = allJobs$relDoneTime - x = c() # I wish I knew how to make this work with apply - for ( time in times ) - x = c(x, sum(p(s, e, time))) - x - } - - pending = countJobs(function(s, e, t) s > t) - done = countJobs(function(s, e, t) e < t) - running = nJobs - pending - done - - d = data.frame(times=times, pending=pending, running=running, done=done) - - p <- ggplot(data=melt(d, id.vars=c("times")), aes(x=times, y=value, color=variable)) - p <- p + facet_grid(variable ~ ., scales="free") - p <- p + geom_line(size=2) - p <- p + xlab(paste("Time since start of first job", RUNTIME_UNITS)) - p <- p + ggtitle("Job scheduling") - print(p) -} - -# -# Creates tables for each job in this group -# -standardColumns = c("jobName", "startTime", "formattedStartTime", "analysisName", "intermediate", "exechosts", "formattedDoneTime", "doneTime", "runtime") -plotGroup <- function(groupTable) { - name = unique(groupTable$analysisName)[1] - groupAnnotations = setdiff(names(groupTable), standardColumns) - sub = groupTable[,c("jobName", groupAnnotations, "runtime")] - sub = sub[order(sub$iteration, sub$jobName, decreasing=F), ] - - # create a table showing each job and all annotations - textplot(sub, show.rownames=F) - title(paste("Job summary for", name, "full itemization"), cex=3) - - # create the table for each combination of values in the group, listing iterations in the columns - sum = cast(melt(sub, id.vars=groupAnnotations, measure.vars=c("runtime")), ... ~ iteration, fun.aggregate=mean) - textplot(as.data.frame(sum), show.rownames=F) - title(paste("Job summary for", name, "itemizing each iteration"), cex=3) - - # histogram of job times by groupAnnotations - if ( length(groupAnnotations) == 1 && dim(sub)[1] > 1 ) { - # todo -- how do we group by annotations? - p <- ggplot(data=sub, aes(x=runtime)) + geom_histogram() - p <- p + xlab(paste("runtime", RUNTIME_UNITS)) + ylab("No. of jobs") - p <- p + ggtitle(paste("Job runtime histogram for", name)) - print(p) - } - - # as above, but averaging over all iterations - groupAnnotationsNoIteration = setdiff(groupAnnotations, "iteration") - if ( dim(sub)[1] > 1 ) { - try({ # need a try here because we will fail to reduce when there's just a single iteration - sum = cast(melt(sub, id.vars=groupAnnotationsNoIteration, measure.vars=c("runtime")), ... ~ ., fun.aggregate=c(mean, sd)) - textplot(as.data.frame(sum), show.rownames=F) - title(paste("Job summary for", name, "averaging over all iterations"), cex=3) - }, silent=T) - } -} - -# print out some useful basic information -print("Report") -print(paste("Project :", inputFileName)) - -convertUnits <- function(gatkReportData) { - convertGroup <- function(g) { - g$runtime = g$runtime * ORIGINAL_UNITS_TO_RUNTIME_UNITS - g$startTime = g$startTime * ORIGINAL_UNITS_TO_RUNTIME_UNITS - g$doneTime = g$doneTime * ORIGINAL_UNITS_TO_RUNTIME_UNITS - g - } - lapply(gatkReportData, convertGroup) -} - -# -# Plots runtimes by analysis name and exechosts -# -# Useful to understand the performance of analysis jobs by hosts, -# and to debug problematic nodes -# -plotTimeByHost <- function(gatkReportData) { - fields = c("analysisName", "exechosts", "runtime") - - runtimes = data.frame() - for ( report in gatkReportData ) { - runtimes = rbind(runtimes, report[,fields]) - } - - plotMe <- function(name, vis) { - p = ggplot(data=runtimes, aes(x=exechosts, y=runtime, group=exechosts, color=exechosts)) - p = p + facet_grid(analysisName ~ ., scale="free") - p = p + vis() - p = p + xlab("Job execution host") - p = p + ggtitle(paste(name, "of job runtimes by analysis name and execution host")) - p = p + ylab(paste("Distribution of runtimes", RUNTIME_UNITS)) - p = p + theme(axis.text.x=element_text(angle=45, hjust=1, vjust=1)) - print(p) - } - - plotMe("Boxplot", geom_boxplot) - plotMe("Jittered points", geom_jitter) -} - -mergeScattersForAnalysis <- function(table) { - #allJobs$ganttName = paste(allJobs$jobName, "@", allJobs$exechosts) - - ddply(table, .(analysisName, iteration), summarize, - jobName = analysisName[1], - exechosts = paste(length(exechosts), "hosts"), - formattedStartTime = "NA", - formattedDoneTime = "NA", - intermediate = intermediate[1], - startTime = min(startTime), - doneTime = min(startTime) + sum(runtime), - runtime = sum(runtime)) -} - -mergeScatters <- function(report) { - newReport = list() - for ( name in names(gatkReportData) ) { - newReport[[name]] = mergeScattersForAnalysis(gatkReportData[[name]]) - } - newReport -} - -# read the table -gatkReportData <- gsa.read.gatkreport(inputFileName) -gatkReportData <- convertUnits(gatkReportData) -#print(summary(gatkReportData)) - -if ( ! is.na(outputPDF) ) { - pdf(outputPDF, height=8.5, width=11) -} - -plotJobsGantt(gatkReportData, T, "All jobs, by analysis, by start time", F) -plotJobsGantt(gatkReportData, F, "All jobs, sorted by start time", F) -plotProgressByTime(gatkReportData) - -# plots summarizing overall costs, merging scattered counts -merged.by.scatter = mergeScatters(gatkReportData) -plotJobsGantt(merged.by.scatter, F, "Jobs merged by scatter by start time", T) - -merged.as.df = do.call(rbind.data.frame, merged.by.scatter)[,c("analysisName", "runtime")] -merged.as.df$percent = merged.as.df$runtime / sum(merged.as.df$runtime) * 100 -merged.as.df.formatted = data.frame(analysisName=merged.as.df$analysisName,runtime=prettyNum(merged.as.df$runtime), percent=prettyNum(merged.as.df$percent,digits=2)) -textplot(merged.as.df.formatted[order(merged.as.df$runtime),], show.rownames=F) -title("Total runtime for each analysis") - -plotTimeByHost(gatkReportData) -for ( group in gatkReportData ) { - #print(group) - plotGroup(group) -} - -if ( ! is.na(outputPDF) ) { - dev.off() - if (exists("compactPDF")) { - compactPDF(outputPDF) - } -} diff --git a/public/biopet-framework/src/main/resources/picard/analysis/baseDistributionByCycle.R b/public/biopet-framework/src/main/resources/picard/analysis/baseDistributionByCycle.R deleted file mode 100644 index e4430689199353dc39d175d14533f4636df3a2bb..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/baseDistributionByCycle.R +++ /dev/null @@ -1,52 +0,0 @@ -# Script to generate a chart of the base distribution by cycle -# @author Nils Homer - -# Parse the arguments -args <- commandArgs(trailing=T); -metricsFile <- args[1]; -outputFile <- args[2]; -bamFile <- args[3]; -subtitle <- ifelse(length(args) < 4, "", args[4]); - - -# Figure out where the metrics and the histogram are in the file and parse them out -startFinder <- scan(metricsFile, what="character", sep="\n", quiet=TRUE, blank.lines.skip=FALSE); - -firstBlankLine=0; - -for (i in 1:length(startFinder)) { - if (startFinder[i] == "") { - if (firstBlankLine==0) { - firstBlankLine=i+1; - } else { - secondBlankLine=i+1; - break; - } - } -} - -metrics <- read.table(metricsFile, header=T, sep="\t", skip=firstBlankLine); - -# Then plot the histogram as a PDF -pdf(outputFile); - -plot(x=c(1, 20+nrow(metrics)), - y=c(0, max(metrics[,3:7])), - main=paste("Base Distribution by Cycle\nin file ",bamFile," ",ifelse(subtitle == "","",paste("(",subtitle,")",sep="")),sep=""), - xlab="Cycle", - ylab="Base Percentage", - type="n"); - -colors = c("red", "orange", "blue", "purple", "black"); - -for (i in 1:5) { - lines(x=1:nrow(metrics), - y=metrics[,2+i], - col=colors[i], - type="l", - lty=1); -} - -legend("bottomright", lwd=1, legend=c("PCT_A", "PCT_C", "PCT_G", "PCT_T", "PCT_N"), col=colors); - -dev.off(); diff --git a/public/biopet-framework/src/main/resources/picard/analysis/gcBias.R b/public/biopet-framework/src/main/resources/picard/analysis/gcBias.R deleted file mode 100644 index 1563cdf36dc0e1cb167a77a988c133e29e76139e..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/gcBias.R +++ /dev/null @@ -1,77 +0,0 @@ -# Script to generate a chart to display GC bias based upon read starts observed -# in windows along the genome. -# -# @author Tim Fennell - -# Parse the arguments -args <- commandArgs(trailing=T) -metricsFile <- args[1] -outputFile <- args[2] -datasetName <- args[3] -subtitle <- args[4] -windowSize <- args[5] - -# Figure out where the metrics and the histogram are in the file and parse them out -startFinder <- scan(metricsFile, what="character", sep="\n", quiet=TRUE, blank.lines.skip=FALSE) - -firstBlankLine=0 - -for (i in 1:length(startFinder)) { - if (startFinder[i] == "") { - if (firstBlankLine==0) { - firstBlankLine=i+1 - } else { - secondBlankLine=i+1 - break - } - } -} - -metrics <- read.table(metricsFile, header=T, sep="\t", skip=firstBlankLine) -pdf(outputFile) - -# Some constants that are used below -Y_AXIS_LIM = 2; -MAX_QUALITY_SCORE = 40; -COLORS = c("royalblue", "#FFAAAA", "palegreen3"); - -# Adjust to give more margin on the right hand side -par(mar = c(5, 4, 4, 4)); - -# Do the main plot of the normalized coverage by GC -plot(type="p", x=metrics$GC, y=metrics$NORMALIZED_COVERAGE, - xlab=paste(c("GC% of", windowSize, "base windows"), sep=" ", collapse=" "), - ylab="Fraction of normalized coverage", - xlim=c(0,100), - ylim=c(0, Y_AXIS_LIM), - col=COLORS[1], - main=paste(datasetName, "GC Bias Plot", "\n", subtitle) - ); - -# Add lines at the 50% GC and coverage=1 -abline(h=1, v=50, col="lightgrey"); - -# Add error bars -arrows(metrics$GC, - metrics$NORMALIZED_COVERAGE - metrics$ERROR_BAR_WIDTH, - metrics$GC, - metrics$NORMALIZED_COVERAGE + metrics$ERROR_BAR_WIDTH, - code = 3, angle = 90, length = 0.05, col="grey"); - -# Plot count of windows as a separate series near the bottom -window_ratio = 0.5 / max(metrics$WINDOWS); -scaled_windows = metrics$WINDOWS * window_ratio; -lines(metrics$GC, scaled_windows, type="h", col=COLORS[2], lwd=3); - -# Plot the quality series -lines(metrics$GC, metrics$MEAN_BASE_QUALITY * Y_AXIS_LIM / MAX_QUALITY_SCORE, type="l", col=COLORS[3]); -axis(4, - at=c(0, Y_AXIS_LIM/4, Y_AXIS_LIM/4*2, Y_AXIS_LIM/4*3, Y_AXIS_LIM), - labels=c(0, MAX_QUALITY_SCORE/4, MAX_QUALITY_SCORE/4*2, MAX_QUALITY_SCORE/4*3, MAX_QUALITY_SCORE) - ); -mtext("Mean base quality", side=4, line=2.5); - -# And finally add a legend -legend("topleft", pch=c(1,15, 45), legend=c("Normalized Coverage", "Windows at GC%", "Base Quality at GC%"), col=COLORS) - -dev.off(); \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/picard/analysis/insertSizeHistogram.R b/public/biopet-framework/src/main/resources/picard/analysis/insertSizeHistogram.R deleted file mode 100644 index a2cdd32011ed2e5c15da71205589a23e5f7be39a..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/insertSizeHistogram.R +++ /dev/null @@ -1,98 +0,0 @@ -## script to generate histogram of insert sizes from metrics file -## expecting 3 arguments: -## first is the metrics file with the histogram info -## second is the output file -## third is a name for the plot - -args <- commandArgs(trailing=TRUE) -metricsFile <- args[1] -pdfFile <- args[2] -bamName <- args[3] -histoWidth <- ifelse(length(args) < 4, 0, as.numeric(args[4])) - -startFinder <- scan(metricsFile, what="character", sep="\n", quiet=TRUE, blank.lines.skip=FALSE) - -firstBlankLine=0 - -for (i in 1:length(startFinder)) { - if (startFinder[i] == "") { - if (firstBlankLine==0) { - firstBlankLine=i+1 - } else { - secondBlankLine=i+1 - break - } - } -} - -histogram <- read.table(metricsFile, header=TRUE, sep="\t", skip=secondBlankLine, comment.char="", quote='', check.names=FALSE) - -## The histogram has a fr_count/rf_count/tandem_count for each metric "level" -## This code parses out the distinct levels so we can output one graph per level -headers <- sapply(sub(".fr_count","",names(histogram),fixed=TRUE), "[[" ,1) -headers <- sapply(sub(".rf_count","",headers,fixed=TRUE), "[[" ,1) -headers <- sapply(sub(".tandem_count","",headers,fixed=TRUE), "[[" ,1) - -## Duplicated header names cause this to barf. KT & Yossi report that this is going to be extremely difficult to -## resolve and it's unlikely that anyone cares anyways. Trap this situation and avoid the PDF so it won't cause -## the workflow to fail -if (any(duplicated(headers))) { - print(paste("Not creating insert size PDF as there are duplicated header names:", headers[which(duplicated(headers))])) -} else { - levels <- c() - for (i in 2:length(headers)) { - if (!(headers[i] %in% levels)) { - levels[length(levels)+1] <- headers[i] - } - } - - pdf(pdfFile) - - for (i in 1:length(levels)) { - ## Reconstitutes the histogram column headers for this level - fr <- paste(levels[i], "fr_count", sep=".") - rf <- paste(levels[i], "rf_count", sep=".") - tandem <- paste(levels[i], "tandem_count", sep=".") - - frrange = ifelse(fr %in% names(histogram), max(histogram[fr]), 0) - rfrange = ifelse(rf %in% names(histogram), max(histogram[rf]), 0) - tandemrange = ifelse(tandem %in% names(histogram), max(histogram[tandem]), 0) - - yrange <- max(frrange, rfrange, tandemrange) - xrange <- ifelse(histoWidth > 0, histoWidth, max(histogram$insert_size)) - - plot(x=NULL, y=NULL, - type="n", - main=paste("Insert Size Histogram for", levels[i], "\nin file", bamName), - xlab="Insert Size", - ylab="Count", - xlim=range(0, xrange), - ylim=range(0, yrange)) - - colors <- c() - labels <- c() - - if (fr %in% names(histogram) ) { - lines(histogram$insert_size, as.matrix(histogram[fr]), type="h", col="red") - colors <- c(colors, "red") - labels <- c(labels, "FR") - } - if (rf %in% names(histogram)) { - lines(histogram$insert_size, as.matrix(histogram[rf]), type="h", col="blue") - colors <- c(colors, "blue") - labels <- c(labels, "RF") - } - - if (tandem %in% names(histogram)) { - lines(histogram$insert_size, as.matrix(histogram[tandem]), type="h", col="orange") - colors <- c(colors, "orange") - labels <- c(labels, "TANDEM") - } - - ## Create the legend - legend("topright", labels, fill=colors, col=colors, cex=0.7) - } - - dev.off() -} - diff --git a/public/biopet-framework/src/main/resources/picard/analysis/meanQualityByCycle.R b/public/biopet-framework/src/main/resources/picard/analysis/meanQualityByCycle.R deleted file mode 100755 index 679e2b42d4e12ab507b18e652bc43224d5473da0..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/meanQualityByCycle.R +++ /dev/null @@ -1,59 +0,0 @@ -# Script to generate a chart of mean quality by cycle from a BAM file -# @author Tim Fennell - -# Parse the arguments -args <- commandArgs(trailing=T) -metricsFile <- args[1] -outputFile <- args[2] -bamFile <- args[3] -subtitle <- ifelse(length(args) < 4, "", args[4]) - - -# Figure out where the metrics and the histogram are in the file and parse them out -startFinder <- scan(metricsFile, what="character", sep="\n", quiet=TRUE, blank.lines.skip=FALSE) - -firstBlankLine=0 - -for (i in 1:length(startFinder)) -{ - if (startFinder[i] == "") { - if (firstBlankLine==0) { - firstBlankLine=i+1 - } else { - secondBlankLine=i+1 - break - } - } -} - -metrics <- read.table(metricsFile, header=T, nrows=1, sep="\t", skip=firstBlankLine) -histogram <- read.table(metricsFile, header=T, sep="\t", skip=secondBlankLine) - -# Then plot the histogram as a PDF -pdf(outputFile) - -plot(histogram$CYCLE, - histogram$MEAN_QUALITY, - type="n", - main=paste("Quality by Cycle\nin file ",bamFile," ",ifelse(subtitle == "","",paste("(",subtitle,")",sep="")),sep=""), - xlab="Cycle", - ylab="Mean Quality", - ylim=range(0,50)) - -qColor <- "darkblue" -oqColor <- rgb(1, 0.25, 0.25, 0.75) - -# Plot OQ first so that it's "behind" the regular qualities -if (!is.null(histogram$MEAN_ORIGINAL_QUALITY)) { - lines(histogram$CYCLE, histogram$MEAN_ORIGINAL_QUALITY, type="l", col=oqColor, lty=1); -} - -# Then plot the regular qualities -lines(histogram$CYCLE, histogram$MEAN_QUALITY, type="h", col=qColor, lty=1); - -# And add a legend -legend("topleft", pch=c(15,15), legend=c("Mean Quality", "Mean Original Quality"), col=c(qColor, oqColor)) - - -dev.off() - diff --git a/public/biopet-framework/src/main/resources/picard/analysis/qualityScoreDistribution.R b/public/biopet-framework/src/main/resources/picard/analysis/qualityScoreDistribution.R deleted file mode 100755 index ced1f8c0ab82842afe00f0abab84c3d575d18d1d..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/qualityScoreDistribution.R +++ /dev/null @@ -1,57 +0,0 @@ -# Script to generate a chart of quality score distribution in a file -# @author Tim Fennell - -# Parse the arguments -args <- commandArgs(trailing=T) -metricsFile <- args[1] -outputFile <- args[2] -bamFile <- args[3] -subtitle <- ifelse(length(args) < 4, "", args[4]) - -# Figure out where the metrics and the histogram are in the file and parse them out -startFinder <- scan(metricsFile, what="character", sep="\n", quiet=TRUE, blank.lines.skip=FALSE) - -firstBlankLine=0 - -for (i in 1:length(startFinder)) -{ - if (startFinder[i] == "") { - if (firstBlankLine==0) { - firstBlankLine=i+1 - } else { - secondBlankLine=i+1 - break - } - } -} - -metrics <- read.table(metricsFile, header=T, nrows=1, sep="\t", skip=firstBlankLine) -histogram <- read.table(metricsFile, header=T, sep="\t", skip=secondBlankLine) - -# Then plot the histogram as a PDF -pdf(outputFile) - -plot(histogram$QUALITY, - histogram$COUNT_OF_Q, - type="n", - main=paste("Quality Score Distribution\nin file ",bamFile," ",ifelse(subtitle == "","",paste("(",subtitle,")",sep="")),sep=""), - xlab="Quality Score", - ylab="Observations") - -qColor <- "blue" -oqColor <- "lightcyan2" -width <- 5 - -# Plot OQ first so that it's "behind" the regular qualities -if (!is.null(histogram$COUNT_OF_OQ)) { - lines(histogram$QUALITY+0.25, histogram$COUNT_OF_OQ, type="h", col=oqColor, lty=1, lwd=width, lend="square"); -} - -# Then plot the regular qualities -lines(histogram$QUALITY, histogram$COUNT_OF_Q, type="h", col=qColor, lty=1, lwd=width, lend="square"); - -# And add a legend -legend("topleft", pch=c(15,15), legend=c("Quality Scores", "Original Quality Scores"), col=c(qColor, oqColor)) - -dev.off() - diff --git a/public/biopet-framework/src/main/resources/picard/analysis/rnaSeqCoverage.R b/public/biopet-framework/src/main/resources/picard/analysis/rnaSeqCoverage.R deleted file mode 100644 index 1cf004ee3802e8b7e485d3c2b14dbbc8e8cf7fee..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/rnaSeqCoverage.R +++ /dev/null @@ -1,70 +0,0 @@ -# Script to generate a normalized coverage vs. position along transcript plot. -# -# @author Tim Fennell - -# Parse the arguments -args <- commandArgs(trailing = TRUE) -metricsFile <- args[1] -outputFile <- args[2] -bamName <- args[3] -subtitle <- ifelse(length(args) < 4, "", args[4]) - -# Figure out where the metrics and the histogram are in the file and parse them out -startFinder <- scan(metricsFile, what="character", sep="\n", quiet=TRUE, blank.lines.skip=FALSE) - -firstBlankLine=0 - -for (i in 1:length(startFinder)) { - if (startFinder[i] == "") { - if (firstBlankLine==0) { - firstBlankLine=i+1 - } else { - secondBlankLine=i+1 - break - } - } -} - -data <- read.table(metricsFile, header=T, sep="\t", skip=secondBlankLine, check.names=FALSE) - -# The histogram has a normalized_position and normalized_coverage column for each metric "level" -# This code parses out the distinct levels so we can output one graph per level -headers <- sapply(sub(".normalized_coverage","",names(data),fixed=TRUE), "[[" ,1) - -## Duplicated header names cause this to barf. KT & Yossi report that this is going to be extremely difficult to -## resolve and it's unlikely that anyone cares anyways. Trap this situation and avoid the PDF so it won't cause -## the workflow to fail -if (any(duplicated(headers))) { - print(paste("Not creating insert size PDF as there are duplicated header names:", headers[which(duplicated(headers))])) -} else { - pdf(outputFile) - levels <- c() - for (i in 2:length(headers)) { - if (!(headers[i] %in% levels)) { - levels[length(levels)+1] <- headers[i] - } - } - - # Some constants that are used below - COLORS = c("royalblue", "#FFAAAA", "palegreen3"); - - # For each level, plot of the normalized coverage by GC - for (i in 1:length(levels)) { - - # Reconstitutes the histogram column header for this level - nc <- paste(levels[i], "normalized_coverage", sep=".") - - plot(x=data$normalized_position, y=as.matrix(data[nc]), - type="o", - xlab="Normalized Distance Along Transcript", - ylab="Normalized Coverage", - xlim=c(0, 100), - ylim=range(0, max(data[nc])), - col="royalblue", - main=paste("RNA-Seq Coverage vs. Transcript Position\n", levels[i], " ", ifelse(subtitle=="", "", paste("(", subtitle, ")", sep="")), "\nin file ", bamName,sep="")) - - # Add a horizontal line at coverage=1 - abline(h=1, col="lightgrey"); - } - dev.off(); -} \ No newline at end of file diff --git a/public/biopet-framework/src/main/resources/picard/analysis/rrbsQc.R b/public/biopet-framework/src/main/resources/picard/analysis/rrbsQc.R deleted file mode 100644 index c7d7abeee2c88223faddf2621f0757bdfe6123e0..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/resources/picard/analysis/rrbsQc.R +++ /dev/null @@ -1,109 +0,0 @@ -## -## The MIT License -## -## Copyright (c) 2013 The Broad Institute -## -## Permission is hereby granted, free of charge, to any person obtaining a copy -## of this software and associated documentation files (the "Software"), to deal -## in the Software without restriction, including without limitation the rights -## to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -## copies of the Software, and to permit persons to whom the Software is -## furnished to do so, subject to the following conditions: -## -## The above copyright notice and this permission notice shall be included in -## all copies or substantial portions of the Software. -## -## THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -## IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -## FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -## AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -## LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -## OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN -## THE SOFTWARE. -## - -args = commandArgs(trailingOnly=TRUE) -opt = list(details.fn=args[1], summary.fn=args[2], output.fn=args[3]) - -read_metrics_file = function(metrics.fn) { - contents = read.delim(metrics.fn, comment.char="#", stringsAsFactors=FALSE) - return(contents) -} - -equals_or_is_na = function(x1, x2) { - if (is.na(x1)) { - return(is.na(x2)) - } else { - return(x1 == x2) - } -} - -details = read_metrics_file(opt$details.fn) -summary = read_metrics_file(opt$summary.fn) - -pdf(opt$output.fn) -par(mfrow=c(2,2), oma=c(0,0,2,0)) - -for (i in seq_len(nrow(summary))) { - cur_summary = summary[i, ] - cur_sample = cur_summary[1, "SAMPLE"] - cur_library = cur_summary[1, "LIBRARY"] - cur_read_group = cur_summary[1, "READ_GROUP"] - cur_details = details[which((equals_or_is_na(cur_library, details[, "LIBRARY"]) & - (equals_or_is_na(cur_sample, details[, "SAMPLE"])) & - (equals_or_is_na(cur_read_group, details[, "READ_GROUP"])))), ] - - - ## Plot conversion rates - cpg.converted = sum(cur_details$CONVERTED_SITES) - cpg.seen = sum(cur_details$TOTAL_SITES) - cpg.conversion = cpg.converted / cpg.seen - total.conversion = (cpg.converted + cur_summary$NON_CPG_CONVERTED_BASES) / (cpg.seen + cur_summary$NON_CPG_BASES) - - barplot(c("non-CpG"=cur_summary$PCT_NON_CPG_BASES_CONVERTED, "Combined"=total.conversion, "CpG"=cpg.conversion), - ylim=c(0.95, 1), ylab="% Conversion", xlab="Distribution", main="Bisulfite Conversion Rate", - col="blue", xpd=FALSE) - abline(h=0.995, col="grey") - - ## Plot histogram of CpG counts by conversion rate - hist(cur_details$PCT_CONVERTED, 10, xlab="Conversion Rate Of CpGs", ylab="# CpGs", - main="CpG Conversion Rate Distribution", col="blue") - - ## Plot pie chart showing distribution of CpG coverage - coverage_breaks = c(0, 1, 5, 10, 25, 50, 100, Inf) - coverage_cut = cut(cur_details$TOTAL_SITES, coverage_breaks) - cpg_coverage = split(cur_details$TOTAL_SITES, coverage_cut) - coverages = sapply(cpg_coverage, length)[2:7] - names(coverages) = paste(">=", c(1, 5, 10, 25, 50, 100), sep="") - ## If we have 0s all across the pie chart will be effectively meaningless but put in a 100% >= 0 field instead - ## to avoid an error on pie(). Normally it'd just be a pain to see these, but ... - if (all(coverages == 0)) { - coverages = c("No Coverage"=1) - } - color_ramp = colorRampPalette(c("white", "#538ED5", "blue"), bias=1, space="Lab") - colors = color_ramp(length(coverages))[2:length(coverages)] - pie(coverages, main="Distribution Of CpGs By Coverage", col=colors, clockwise=TRUE) - - discards = log10(c("Mismatches"=cur_summary$READS_IGNORED_MISMATCHES, "Size"=cur_summary$READS_IGNORED_SHORT)) - ## Protect against -Inf in the case where we had 0 discards - discards = ifelse(is.finite(discards), discards, 0) - barplot(discards, ylab="Number Discarded (log10)", xlab="Reason", - main="Reads Discarded", col="blue", ylim=c(0, ceiling(max(discards)))) - - header_txt = character() - if (!is.na(cur_sample) && cur_sample != "") { - header_txt = paste(header_txt, " SAMPLE=", cur_sample, sep="") - } - if (!is.na(cur_library) && cur_library != "") { - header_txt = paste(header_txt, " LIBRARY=", cur_library, sep="") - } - if (!is.na(cur_read_group) && cur_read_group != "") { - header_txt = paste(header_txt, " READ GROUP=", cur_read_group, sep="") - } - if (length(header_txt) > 0) { - mtext(header_txt, outer=TRUE, line=1) - } -} - -dev.off() - diff --git a/public/biopet-framework/src/main/scala/nl/lumc/sasc/biopet/pipelines/MultisamplePipelineTemplate.scala b/public/biopet-framework/src/main/scala/nl/lumc/sasc/biopet/pipelines/MultisamplePipelineTemplate.scala deleted file mode 100644 index 2c8cf37b5c45eedff6f7a7c501e88e0a8826f8bf..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/scala/nl/lumc/sasc/biopet/pipelines/MultisamplePipelineTemplate.scala +++ /dev/null @@ -1,81 +0,0 @@ -/** - * Biopet is built on top of GATK Queue for building bioinformatic - * pipelines. It is mainly intended to support LUMC SHARK cluster which is running - * SGE. But other types of HPC that are supported by GATK Queue (such as PBS) - * should also be able to execute Biopet tools and pipelines. - * - * Copyright 2014 Sequencing Analysis Support Core - Leiden University Medical Center - * - * Contact us at: sasc@lumc.nl - * - * A dual licensing mode is applied. The source code within this project that are - * not part of GATK Queue is freely available for non-commercial use under an AGPL - * license; For commercial users or users who do not want to follow the AGPL - * license, please contact us to obtain a separate license. - */ -package nl.lumc.sasc.biopet.pipelines - -import nl.lumc.sasc.biopet.utils.config.Configurable -import nl.lumc.sasc.biopet.core.{ MultiSampleQScript, PipelineCommand } -import org.broadinstitute.gatk.queue.QScript - -/** Template for a multisample pipeline */ -class MultisamplePipelineTemplate(val root: Configurable) extends QScript with MultiSampleQScript { - def this() = this(null) - - /** Location of summary file */ - def summaryFile: File = new File(outputDir, "MultisamplePipelineTemplate.summary.json") - - /** File to add to the summary */ - def summaryFiles: Map[String, File] = Map() - - /** Pipeline settings to add to the summary */ - def summarySettings: Map[String, Any] = Map() - - /** Function to make a sample */ - def makeSample(id: String) = new Sample(id) - - /** This class will contain jobs and libraries for a sample */ - class Sample(sampleId: String) extends AbstractSample(sampleId) { - /** Sample specific files for summary */ - def summaryFiles: Map[String, File] = Map() - - /** Sample specific stats for summary */ - def summaryStats: Map[String, Any] = Map() - - /** Function to make a library */ - def makeLibrary(id: String) = new Library(id) - - /** This class will contain all jobs for a library */ - class Library(libId: String) extends AbstractLibrary(libId) { - /** Library specific files for summary */ - def summaryFiles: Map[String, File] = Map() - - /** Library specific stats for summary */ - def summaryStats: Map[String, Any] = Map() - - /** Method to add library jobs */ - protected def addJobs(): Unit = { - } - } - - /** Method to add sample jobs */ - protected def addJobs(): Unit = { - } - } - - /** Method where multisample jobs are added */ - def addMultiSampleJobs(): Unit = { - } - - /** This is executed before the script starts */ - def init(): Unit = { - } - - /** Method where jobs must be added */ - def biopetScript() { - } -} - -/** Object to let to generate a main method */ -object MultisamplePipelineTemplate extends PipelineCommand \ No newline at end of file diff --git a/public/biopet-framework/src/main/scala/nl/lumc/sasc/biopet/pipelines/PipelineTemplate.scala b/public/biopet-framework/src/main/scala/nl/lumc/sasc/biopet/pipelines/PipelineTemplate.scala deleted file mode 100644 index d15e99f882245b16a086833a014a61627e905330..0000000000000000000000000000000000000000 --- a/public/biopet-framework/src/main/scala/nl/lumc/sasc/biopet/pipelines/PipelineTemplate.scala +++ /dev/null @@ -1,36 +0,0 @@ -/** - * Biopet is built on top of GATK Queue for building bioinformatic - * pipelines. It is mainly intended to support LUMC SHARK cluster which is running - * SGE. But other types of HPC that are supported by GATK Queue (such as PBS) - * should also be able to execute Biopet tools and pipelines. - * - * Copyright 2014 Sequencing Analysis Support Core - Leiden University Medical Center - * - * Contact us at: sasc@lumc.nl - * - * A dual licensing mode is applied. The source code within this project that are - * not part of GATK Queue is freely available for non-commercial use under an AGPL - * license; For commercial users or users who do not want to follow the AGPL - * license, please contact us to obtain a separate license. - */ -package nl.lumc.sasc.biopet.pipelines - -import nl.lumc.sasc.biopet.utils.config.Configurable -import nl.lumc.sasc.biopet.core.{ BiopetQScript, PipelineCommand } -import org.broadinstitute.gatk.queue.QScript - -/** Template for a pipeline */ -class PipelineTemplate(val root: Configurable) extends QScript with BiopetQScript { - def this() = this(null) - - /** This is executed before the script starts */ - def init() { - } - - /** Method where jobs must be added */ - def biopetScript() { - } -} - -/** Object to let to generate a main method */ -object PipelineTemplate extends PipelineCommand