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added:
differential_count_models/.hg_archival.txt differential_count_models/rgToolFactory.py differential_count_models/rgedgeRpaired.xml.camera differential_count_models/rgedgeRpaired_nocamera.xml differential_count_models/test-data/edgeRtest1out.html differential_count_models/test-data/edgeRtest1out.xls differential_count_models/test-data/gentestdata.sh differential_count_models/test-data/test_bams2mx.xls differential_count_models/tool_dependencies.xml |
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removed:
rgToolFactory.py rgedgeRpaired.xml.camera rgedgeRpaired_nocamera.xml test-data/edgeRtest1out.html test-data/edgeRtest1out.xls test-data/gentestdata.sh test-data/test_bams2mx.xls tool_dependencies.xml |
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| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/.hg_archival.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/.hg_archival.txt Wed Aug 07 23:49:40 2013 -0400 |
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| @@ -0,0 +1,5 @@ +repo: 2122e630b13aedc43ced5f83c11988903db28ea6 +node: 37b851eb82033c12fdb550e847e8b40ee302b3c8 +branch: default +latesttag: null +latesttagdistance: 24 |
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| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/rgToolFactory.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/rgToolFactory.py Wed Aug 07 23:49:40 2013 -0400 |
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| b'@@ -0,0 +1,631 @@\n+# rgToolFactory.py\n+# see https://bitbucket.org/fubar/galaxytoolfactory/wiki/Home\n+# \n+# copyright ross lazarus (ross stop lazarus at gmail stop com) May 2012\n+# \n+# all rights reserved\n+# Licensed under the LGPL\n+# suggestions for improvement and bug fixes welcome at https://bitbucket.org/fubar/galaxytoolfactory/wiki/Home\n+#\n+# august 2013\n+# found a problem with GS if $TMP or $TEMP missing - now inject /tmp and warn\n+#\n+# july 2013\n+# added ability to combine images and individual log files into html output\n+# just make sure there\'s a log file foo.log and it will be output\n+# together with all images named like "foo_*.pdf\n+# otherwise old format for html\n+#\n+# January 2013\n+# problem pointed out by Carlos Borroto\n+# added escaping for <>$ - thought I did that ages ago...\n+#\n+# August 11 2012 \n+# changed to use shell=False and cl as a sequence\n+\n+# This is a Galaxy tool factory for simple scripts in python, R or whatever ails ye.\n+# It also serves as the wrapper for the new tool.\n+# \n+# you paste and run your script\n+# Only works for simple scripts that read one input from the history.\n+# Optionally can write one new history dataset,\n+# and optionally collect any number of outputs into links on an autogenerated HTML page.\n+\n+# DO NOT install on a public or important site - please.\n+\n+# installed generated tools are fine if the script is safe.\n+# They just run normally and their user cannot do anything unusually insecure\n+# but please, practice safe toolshed.\n+# Read the fucking code before you install any tool \n+# especially this one\n+\n+# After you get the script working on some test data, you can\n+# optionally generate a toolshed compatible gzip file\n+# containing your script safely wrapped as an ordinary Galaxy script in your local toolshed for\n+# safe and largely automated installation in a production Galaxy.\n+\n+# If you opt for an HTML output, you get all the script outputs arranged\n+# as a single Html history item - all output files are linked, thumbnails for all the pdfs.\n+# Ugly but really inexpensive.\n+# \n+# Patches appreciated please. \n+#\n+#\n+# long route to June 2012 product\n+# Behold the awesome power of Galaxy and the toolshed with the tool factory to bind them\n+# derived from an integrated script model \n+# called rgBaseScriptWrapper.py\n+# Note to the unwary:\n+# This tool allows arbitrary scripting on your Galaxy as the Galaxy user\n+# There is nothing stopping a malicious user doing whatever they choose\n+# Extremely dangerous!!\n+# Totally insecure. So, trusted users only\n+#\n+# preferred model is a developer using their throw away workstation instance - ie a private site.\n+# no real risk. The universe_wsgi.ini admin_users string is checked - only admin users are permitted to run this tool.\n+#\n+\n+import sys \n+import shutil \n+import subprocess \n+import os \n+import time \n+import tempfile \n+import optparse\n+import tarfile\n+import re\n+import shutil\n+import math\n+\n+progname = os.path.split(sys.argv[0])[1] \n+myversion = \'V000.2 June 2012\' \n+verbose = False \n+debug = False\n+toolFactoryURL = \'https://bitbucket.org/fubar/galaxytoolfactory\'\n+\n+def timenow():\n+ """return current time as a string\n+ """\n+ return time.strftime(\'%d/%m/%Y %H:%M:%S\', time.localtime(time.time()))\n+\n+html_escape_table = {\n+ "&": "&",\n+ ">": ">",\n+ "<": "<",\n+ "$": "\\$"\n+ }\n+\n+def html_escape(text):\n+ """Produce entities within text."""\n+ return "".join(html_escape_table.get(c,c) for c in text)\n+\n+def cmd_exists(cmd):\n+ return subprocess.call("type " + cmd, shell=True, \n+ stdout=subprocess.PIPE, stderr=subprocess.PIPE) == 0\n+\n+\n+class ScriptRunner:\n+ """class is a wrapper for an arbitrary script\n+ """\n+\n+ def __init__(self,opts=None,treatbashSpecial=True):\n+ """\n+ cleanup inputs, setup some outputs\n+ \n+ """\n+ self.useGM = cmd_exists(\'gm\')\n+ self.useIM = cmd_exists(\'convert\')\n+ self.useGS = cmd_exists(\'gs\')\n'..b'he display\n+ else:\n+ html.append(\'<div class="warningmessagelarge">### Error - %s returned no files - please confirm that parameters are sane</div>\' % self.opts.interpreter)\n+ html.append(galhtmlpostfix)\n+ htmlf = file(self.opts.output_html,\'w\')\n+ htmlf.write(\'\\n\'.join(html))\n+ htmlf.write(\'\\n\')\n+ htmlf.close()\n+ self.html = html\n+\n+\n+ def run(self):\n+ """\n+ scripts must be small enough not to fill the pipe!\n+ """\n+ if self.treatbashSpecial and self.opts.interpreter in [\'bash\',\'sh\']:\n+ retval = self.runBash()\n+ else:\n+ if self.opts.output_dir:\n+ ste = open(self.elog,\'w\')\n+ sto = open(self.tlog,\'w\')\n+ sto.write(\'## Toolfactory generated command line = %s\\n\' % \' \'.join(self.cl))\n+ sto.flush()\n+ p = subprocess.Popen(self.cl,shell=False,stdout=sto,stderr=ste,stdin=subprocess.PIPE,cwd=self.opts.output_dir)\n+ else:\n+ p = subprocess.Popen(self.cl,shell=False,stdin=subprocess.PIPE)\n+ p.stdin.write(self.script)\n+ p.stdin.close()\n+ retval = p.wait()\n+ if self.opts.output_dir:\n+ sto.close()\n+ ste.close()\n+ err = open(self.elog,\'r\').readlines()\n+ if retval <> 0 and err: # problem\n+ print >> sys.stderr,err\n+ if self.opts.make_HTML:\n+ self.makeHtml()\n+ return retval\n+\n+ def runBash(self):\n+ """\n+ cannot use - for bash so use self.sfile\n+ """\n+ if self.opts.output_dir:\n+ s = \'## Toolfactory generated command line = %s\\n\' % \' \'.join(self.cl)\n+ sto = open(self.tlog,\'w\')\n+ sto.write(s)\n+ sto.flush()\n+ p = subprocess.Popen(self.cl,shell=False,stdout=sto,stderr=sto,cwd=self.opts.output_dir)\n+ else:\n+ p = subprocess.Popen(self.cl,shell=False) \n+ retval = p.wait()\n+ if self.opts.output_dir:\n+ sto.close()\n+ if self.opts.make_HTML:\n+ self.makeHtml()\n+ return retval\n+ \n+\n+def main():\n+ u = """\n+ This is a Galaxy wrapper. It expects to be called by a special purpose tool.xml as:\n+ <command interpreter="python">rgBaseScriptWrapper.py --script_path "$scriptPath" --tool_name "foo" --interpreter "Rscript"\n+ </command>\n+ """\n+ op = optparse.OptionParser()\n+ a = op.add_option\n+ a(\'--script_path\',default=None)\n+ a(\'--tool_name\',default=None)\n+ a(\'--interpreter\',default=None)\n+ a(\'--output_dir\',default=None)\n+ a(\'--output_html\',default=None)\n+ a(\'--input_tab\',default="None")\n+ a(\'--output_tab\',default="None")\n+ a(\'--user_email\',default=\'Unknown\')\n+ a(\'--bad_user\',default=None)\n+ a(\'--make_Tool\',default=None)\n+ a(\'--make_HTML\',default=None)\n+ a(\'--help_text\',default=None)\n+ a(\'--tool_desc\',default=None)\n+ a(\'--new_tool\',default=None)\n+ a(\'--tool_version\',default=None)\n+ opts, args = op.parse_args()\n+ assert not opts.bad_user,\'UNAUTHORISED: %s is NOT authorized to use this tool until Galaxy admin adds %s to admin_users in universe_wsgi.ini\' % (opts.bad_user,opts.bad_user)\n+ assert opts.tool_name,\'## Tool Factory expects a tool name - eg --tool_name=DESeq\'\n+ assert opts.interpreter,\'## Tool Factory wrapper expects an interpreter - eg --interpreter=Rscript\'\n+ assert os.path.isfile(opts.script_path),\'## Tool Factory wrapper expects a script path - eg --script_path=foo.R\'\n+ if opts.output_dir:\n+ try:\n+ os.makedirs(opts.output_dir)\n+ except:\n+ pass\n+ r = ScriptRunner(opts)\n+ if opts.make_Tool:\n+ retcode = r.makeTooltar()\n+ else:\n+ retcode = r.run()\n+ os.unlink(r.sfile)\n+ if retcode:\n+ sys.exit(retcode) # indicate failure to job runner\n+\n+\n+if __name__ == "__main__":\n+ main()\n+\n+\n' |
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| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/rgedgeRpaired.xml.camera --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/rgedgeRpaired.xml.camera Wed Aug 07 23:49:40 2013 -0400 |
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| b'@@ -0,0 +1,1084 @@\n+<tool id="rgDifferentialCount" name="Differential_Count" version="0.20">\n+ <description>models using BioConductor packages</description>\n+ <requirements>\n+ <requirement type="package" version="2.12">biocbasics</requirement>\n+ <requirement type="package" version="3.0.1">r3</requirement>\n+ <requirement type="package" version="1.3.18">graphicsmagick</requirement>\n+ <requirement type="package" version="9.07">ghostscript</requirement>\n+ </requirements>\n+ \n+ <command interpreter="python">\n+ rgToolFactory.py --script_path "$runme" --interpreter "Rscript" --tool_name "DifferentialCounts" \n+ --output_dir "$html_file.files_path" --output_html "$html_file" --make_HTML "yes"\n+ </command>\n+ <inputs>\n+ <param name="input1" type="data" format="tabular" label="Select an input matrix - rows are contigs, columns are counts for each sample"\n+ help="Use the HTSeq based count matrix preparation tool to create these matrices from BAM/SAM files and a GTF file of genomic features"/>\n+ <param name="title" type="text" value="Differential Counts" size="80" label="Title for job outputs" \n+ help="Supply a meaningful name here to remind you what the outputs contain">\n+ <sanitizer invalid_char="">\n+ <valid initial="string.letters,string.digits"><add value="_" /> </valid>\n+ </sanitizer>\n+ </param>\n+ <param name="treatment_name" type="text" value="Treatment" size="50" label="Treatment Name"/>\n+ <param name="Treat_cols" label="Select columns containing treatment." type="data_column" data_ref="input1" numerical="True" \n+ multiple="true" use_header_names="true" size="120" display="checkboxes">\n+ <validator type="no_options" message="Please select at least one column."/>\n+ </param>\n+ <param name="control_name" type="text" value="Control" size="50" label="Control Name"/>\n+ <param name="Control_cols" label="Select columns containing control." type="data_column" data_ref="input1" numerical="True" \n+ multiple="true" use_header_names="true" size="120" display="checkboxes" optional="true">\n+ </param>\n+ <param name="subjectids" type="text" optional="true" size="120" value = ""\n+ label="IF SUBJECTS NOT ALL INDEPENDENT! Enter comma separated strings to indicate sample labels for (eg) pairing - must be one for every column in input"\n+ help="Leave blank if no pairing, but eg if data from sample id A99 is in columns 2,4 and id C21 is in 3,5 then enter \'A99,C21,A99,C21\'">\n+ <sanitizer>\n+ <valid initial="string.letters,string.digits"><add value="," /> </valid>\n+ </sanitizer>\n+ </param>\n+ <param name="fQ" type="float" value="0.3" size="5" label="Non-differential contig count quantile threshold - zero to analyze all non-zero read count contigs"\n+ help="May be a good or a bad idea depending on the biology and the question. EG 0.3 = sparsest 30% of contigs with at least one read are removed before analysis"/>\n+ <param name="useNDF" type="boolean" truevalue="T" falsevalue="F" checked="false" size="1" \n+ label="Non differential filter - remove contigs below a threshold (1 per million) for half or more samples"\n+ help="May be a good or a bad idea depending on the biology and the question. This was the old default. Quantile based is available as an alternative"/>\n+\n+ <conditional name="edgeR">\n+ <param name="doedgeR" type="select" \n+ label="Run this model using edgeR"\n+ help="edgeR uses a negative binomial model and seems to be powerful, even with few replicates">\n+ <option value="F">Do not run edgeR</option>\n+ <option value="T" selected="true">Run edgeR</option>\n+ </param>\n+ <when value="T">\n+ <param name="edgeR_priordf" type="integer" value="20" size="3" \n+ label="prior.df for tagwise dispersion - lower value = more emphasis on each tag\'s variance. Replaces prior.n and prior.df = prior.n * residual.df"\n'..b'Preprint.pdf\n+\n+See Also\n+\n+A voom case study is given in the edgeR User\'s Guide.\n+\n+vooma is a similar function but for microarrays instead of RNA-seq.\n+\n+\n+***old rant on changes to Bioconductor package variable names between versions***\n+\n+The edgeR authors made a small cosmetic change in the name of one important variable (from p.value to PValue) \n+breaking this and all other code that assumed the old name for this variable, \n+between edgeR2.4.4 and 2.4.6 (the version for R 2.14 as at the time of writing). \n+This means that all code using edgeR is sensitive to the version. I think this was a very unwise thing \n+to do because it wasted hours of my time to track down and will similarly cost other edgeR users dearly\n+when their old scripts break. This tool currently now works with 2.4.6.\n+\n+**Note on prior.N**\n+\n+http://seqanswers.com/forums/showthread.php?t=5591 says:\n+\n+*prior.n*\n+\n+The value for prior.n determines the amount of smoothing of tagwise dispersions towards the common dispersion. \n+You can think of it as like a "weight" for the common value. (It is actually the weight for the common likelihood \n+in the weighted likelihood equation). The larger the value for prior.n, the more smoothing, i.e. the closer your \n+tagwise dispersion estimates will be to the common dispersion. If you use a prior.n of 1, then that gives the \n+common likelihood the weight of one observation.\n+\n+In answer to your question, it is a good thing to squeeze the tagwise dispersions towards a common value, \n+or else you will be using very unreliable estimates of the dispersion. I would not recommend using the value that \n+you obtained from estimateSmoothing()---this is far too small and would result in virtually no moderation \n+(squeezing) of the tagwise dispersions. How many samples do you have in your experiment? \n+What is the experimental design? If you have few samples (less than 6) then I would suggest a prior.n of at least 10. \n+If you have more samples, then the tagwise dispersion estimates will be more reliable, \n+so you could consider using a smaller prior.n, although I would hesitate to use a prior.n less than 5. \n+\n+\n+From Bioconductor Digest, Vol 118, Issue 5, Gordon writes:\n+\n+Dear Dorota,\n+\n+The important settings are prior.df and trend.\n+\n+prior.n and prior.df are related through prior.df = prior.n * residual.df,\n+and your experiment has residual.df = 36 - 12 = 24. So the old setting of\n+prior.n=10 is equivalent for your data to prior.df = 240, a very large\n+value. Going the other way, the new setting of prior.df=10 is equivalent\n+to prior.n=10/24.\n+\n+To recover old results with the current software you would use\n+\n+ estimateTagwiseDisp(object, prior.df=240, trend="none")\n+\n+To get the new default from old software you would use\n+\n+ estimateTagwiseDisp(object, prior.n=10/24, trend=TRUE)\n+\n+Actually the old trend method is equivalent to trend="loess" in the new\n+software. You should use plotBCV(object) to see whether a trend is\n+required.\n+\n+Note you could also use\n+\n+ prior.n = getPriorN(object, prior.df=10)\n+\n+to map between prior.df and prior.n.\n+\n+----\n+\n+**Attributions**\n+\n+edgeR - edgeR_ \n+\n+VOOM/limma - limma_VOOM_ \n+\n+DESeq2 - DESeq2_ for details\n+\n+See above for Bioconductor package documentation for packages exposed in Galaxy by this tool and app store package.\n+\n+Galaxy_ (that\'s what you are using right now!) for gluing everything together \n+\n+Otherwise, all code and documentation comprising this tool was written by Ross Lazarus and is \n+licensed to you under the LGPL_ like other rgenetics artefacts\n+\n+.. _LGPL: http://www.gnu.org/copyleft/lesser.html\n+.. _HTSeq: http://www-huber.embl.de/users/anders/HTSeq/doc/index.html\n+.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html\n+.. _DESeq2: http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html\n+.. _limma_VOOM: http://www.bioconductor.org/packages/release/bioc/html/limma.html\n+.. _Galaxy: http://getgalaxy.org\n+</help>\n+\n+</tool>\n+\n+\n' |
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| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/rgedgeRpaired_nocamera.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/rgedgeRpaired_nocamera.xml Wed Aug 07 23:49:40 2013 -0400 |
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| b'@@ -0,0 +1,1072 @@\n+<tool id="rgDifferentialCount" name="Differential_Count" version="0.21">\n+ <description>models using BioConductor packages</description>\n+ <requirements>\n+ <requirement type="package" version="2.12">biocbasics</requirement>\n+ <requirement type="package" version="3.0.1">r3</requirement>\n+ <requirement type="package" version="1.3.18">graphicsmagick</requirement>\n+ <requirement type="package" version="9.07">ghostscript</requirement>\n+ </requirements>\n+ \n+ <command interpreter="python">\n+ rgToolFactory.py --script_path "$runme" --interpreter "Rscript" --tool_name "DifferentialCounts" \n+ --output_dir "$html_file.files_path" --output_html "$html_file" --make_HTML "yes"\n+ </command>\n+ <inputs>\n+ <param name="input1" type="data" format="tabular" label="Select an input matrix - rows are contigs, columns are counts for each sample"\n+ help="Use the HTSeq based count matrix preparation tool to create these matrices from BAM/SAM files and a GTF file of genomic features"/>\n+ <param name="title" type="text" value="Differential Counts" size="80" label="Title for job outputs" \n+ help="Supply a meaningful name here to remind you what the outputs contain">\n+ <sanitizer invalid_char="">\n+ <valid initial="string.letters,string.digits"><add value="_" /> </valid>\n+ </sanitizer>\n+ </param>\n+ <param name="treatment_name" type="text" value="Treatment" size="50" label="Treatment Name"/>\n+ <param name="Treat_cols" label="Select columns containing treatment." type="data_column" data_ref="input1" numerical="True" \n+ multiple="true" use_header_names="true" size="120" display="checkboxes">\n+ <validator type="no_options" message="Please select at least one column."/>\n+ </param>\n+ <param name="control_name" type="text" value="Control" size="50" label="Control Name"/>\n+ <param name="Control_cols" label="Select columns containing control." type="data_column" data_ref="input1" numerical="True" \n+ multiple="true" use_header_names="true" size="120" display="checkboxes" optional="true">\n+ </param>\n+ <param name="subjectids" type="text" optional="true" size="120" value = ""\n+ label="IF SUBJECTS NOT ALL INDEPENDENT! Enter comma separated strings to indicate sample labels for (eg) pairing - must be one for every column in input"\n+ help="Leave blank if no pairing, but eg if data from sample id A99 is in columns 2,4 and id C21 is in 3,5 then enter \'A99,C21,A99,C21\'">\n+ <sanitizer>\n+ <valid initial="string.letters,string.digits"><add value="," /> </valid>\n+ </sanitizer>\n+ </param>\n+ <param name="fQ" type="float" value="0.3" size="5" label="Non-differential contig count quantile threshold - zero to analyze all non-zero read count contigs"\n+ help="May be a good or a bad idea depending on the biology and the question. EG 0.3 = sparsest 30% of contigs with at least one read are removed before analysis"/>\n+ <param name="useNDF" type="boolean" truevalue="T" falsevalue="F" checked="false" size="1" \n+ label="Non differential filter - remove contigs below a threshold (1 per million) for half or more samples"\n+ help="May be a good or a bad idea depending on the biology and the question. This was the old default. Quantile based is available as an alternative"/>\n+\n+ <conditional name="edgeR">\n+ <param name="doedgeR" type="select" \n+ label="Run this model using edgeR"\n+ help="edgeR uses a negative binomial model and seems to be powerful, even with few replicates">\n+ <option value="F">Do not run edgeR</option>\n+ <option value="T" selected="true">Run edgeR</option>\n+ </param>\n+ <when value="T">\n+ <param name="edgeR_priordf" type="integer" value="20" size="3" \n+ label="prior.df for tagwise dispersion - lower value = more emphasis on each tag\'s variance. Replaces prior.n and prior.df = prior.n * residual.df"\n'..b'Preprint.pdf\n+\n+See Also\n+\n+A voom case study is given in the edgeR User\'s Guide.\n+\n+vooma is a similar function but for microarrays instead of RNA-seq.\n+\n+\n+***old rant on changes to Bioconductor package variable names between versions***\n+\n+The edgeR authors made a small cosmetic change in the name of one important variable (from p.value to PValue) \n+breaking this and all other code that assumed the old name for this variable, \n+between edgeR2.4.4 and 2.4.6 (the version for R 2.14 as at the time of writing). \n+This means that all code using edgeR is sensitive to the version. I think this was a very unwise thing \n+to do because it wasted hours of my time to track down and will similarly cost other edgeR users dearly\n+when their old scripts break. This tool currently now works with 2.4.6.\n+\n+**Note on prior.N**\n+\n+http://seqanswers.com/forums/showthread.php?t=5591 says:\n+\n+*prior.n*\n+\n+The value for prior.n determines the amount of smoothing of tagwise dispersions towards the common dispersion. \n+You can think of it as like a "weight" for the common value. (It is actually the weight for the common likelihood \n+in the weighted likelihood equation). The larger the value for prior.n, the more smoothing, i.e. the closer your \n+tagwise dispersion estimates will be to the common dispersion. If you use a prior.n of 1, then that gives the \n+common likelihood the weight of one observation.\n+\n+In answer to your question, it is a good thing to squeeze the tagwise dispersions towards a common value, \n+or else you will be using very unreliable estimates of the dispersion. I would not recommend using the value that \n+you obtained from estimateSmoothing()---this is far too small and would result in virtually no moderation \n+(squeezing) of the tagwise dispersions. How many samples do you have in your experiment? \n+What is the experimental design? If you have few samples (less than 6) then I would suggest a prior.n of at least 10. \n+If you have more samples, then the tagwise dispersion estimates will be more reliable, \n+so you could consider using a smaller prior.n, although I would hesitate to use a prior.n less than 5. \n+\n+\n+From Bioconductor Digest, Vol 118, Issue 5, Gordon writes:\n+\n+Dear Dorota,\n+\n+The important settings are prior.df and trend.\n+\n+prior.n and prior.df are related through prior.df = prior.n * residual.df,\n+and your experiment has residual.df = 36 - 12 = 24. So the old setting of\n+prior.n=10 is equivalent for your data to prior.df = 240, a very large\n+value. Going the other way, the new setting of prior.df=10 is equivalent\n+to prior.n=10/24.\n+\n+To recover old results with the current software you would use\n+\n+ estimateTagwiseDisp(object, prior.df=240, trend="none")\n+\n+To get the new default from old software you would use\n+\n+ estimateTagwiseDisp(object, prior.n=10/24, trend=TRUE)\n+\n+Actually the old trend method is equivalent to trend="loess" in the new\n+software. You should use plotBCV(object) to see whether a trend is\n+required.\n+\n+Note you could also use\n+\n+ prior.n = getPriorN(object, prior.df=10)\n+\n+to map between prior.df and prior.n.\n+\n+----\n+\n+**Attributions**\n+\n+edgeR - edgeR_ \n+\n+VOOM/limma - limma_VOOM_ \n+\n+DESeq2 - DESeq2_ for details\n+\n+See above for Bioconductor package documentation for packages exposed in Galaxy by this tool and app store package.\n+\n+Galaxy_ (that\'s what you are using right now!) for gluing everything together \n+\n+Otherwise, all code and documentation comprising this tool was written by Ross Lazarus and is \n+licensed to you under the LGPL_ like other rgenetics artefacts\n+\n+.. _LGPL: http://www.gnu.org/copyleft/lesser.html\n+.. _HTSeq: http://www-huber.embl.de/users/anders/HTSeq/doc/index.html\n+.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html\n+.. _DESeq2: http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html\n+.. _limma_VOOM: http://www.bioconductor.org/packages/release/bioc/html/limma.html\n+.. _Galaxy: http://getgalaxy.org\n+</help>\n+\n+</tool>\n+\n+\n' |
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| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/test-data/edgeRtest1out.html --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/test-data/edgeRtest1out.html Wed Aug 07 23:49:40 2013 -0400 |
| [ |
| b'@@ -0,0 +1,733 @@\n+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> \n+ <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en"> \n+ <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> \n+ <meta name="generator" content="Galaxy rgToolFactory.py tool output - see http://g2.trac.bx.psu.edu/" /> \n+ <title></title> \n+ <link rel="stylesheet" href="/static/style/base.css" type="text/css" /> \n+ </head> \n+ <body> \n+ <div class="toolFormBody"> \n+ \n+<div class="infomessage">Galaxy Tool "DifferentialCounts" run at 07/08/2013 15:46:55</div><br/>\n+<div class="toolFormTitle">DESeq2 images and outputs</div>\n+(Click on a thumbnail image to download the corresponding original PDF image)<br/>\n+<div><table class="simple" cellpadding="2" cellspacing="2">\n+<tr>\n+<td><a href="DESeq2_MA_plot.pdf"><img src="DESeq2_MA_plot.png" title="Click to download a PDF of DESeq2_MA_plot.pdf" hspace="5" width="400" \n+ alt="Image called DESeq2_MA_plot.pdf"/></a></td>\n+\n+<td><a href="DESeq2_PCA_plot.pdf"><img src="DESeq2_PCA_plot.png" title="Click to download a PDF of DESeq2_PCA_plot.pdf" hspace="5" width="400" \n+ alt="Image called DESeq2_PCA_plot.pdf"/></a></td>\n+\n+<td><a href="DESeq2_dispersion_estimates.pdf"><img src="DESeq2_dispersion_estimates.png" title="Click to download a PDF of DESeq2_dispersion_estimates.pdf" hspace="5" width="400" \n+ alt="Image called DESeq2_dispersion_estimates.pdf"/></a></td>\n+</tr>\n+<tr>\n+<td><a href="DESeq2_qqplot.pdf"><img src="DESeq2_qqplot.png" title="Click to download a PDF of DESeq2_qqplot.pdf" hspace="5" width="400" \n+ alt="Image called DESeq2_qqplot.pdf"/></a></td>\n+\n+<td><a href="DESeq2_sample_distance_plot.pdf"><img src="DESeq2_sample_distance_plot.png" title="Click to download a PDF of DESeq2_sample_distance_plot.pdf" hspace="5" width="400" \n+ alt="Image called DESeq2_sample_distance_plot.pdf"/></a></td>\n+\n+<td> </td>\n+</tr></table></div>\n+\n+<div class="toolFormTitle">DESeq2 log output</div>\n+\n+<pre>\n+\n+# DESeq top 50\n+\n+ Contig baseMean log2FoldChange lfcSE pvalue padj NReads URL\n+\n+Mir192 Mir192 271352.97636 6.965264 0.2150593 4.096936e-230 4.576278e-227 2325567 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir192\'>Mir192</a>\n+\n+Mir122a Mir122a 10112.31117 10.312083 0.3292695 2.649323e-215 1.479647e-212 90428 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir122a\'>Mir122a</a>\n+\n+Mir149 Mir149 810.35429 -6.911118 0.2341392 1.735537e-191 6.461982e-189 6164 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir149\'>Mir149</a>\n+\n+Mir23a Mir23a 1289.18043 -3.104086 0.1191688 1.424246e-149 3.977206e-147 10118 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir23a\'>Mir23a</a>\n+\n+Mir181d Mir181d 275.22797 -3.581172 0.1778187 3.329371e-90 7.437816e-88 2139 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir181d\'>Mir181d</a>\n+\n+Mir204 Mir204 347.57397 -7.284200 0.3771119 3.959336e-83 7.370965e-81 2601 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir204\'>Mir204</a>\n+\n+Mir23b Mir23b 2028.55377 -2.065110 0.1085802 1.182361e-80 1.886711e-78 16387 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir23b\'>Mir23b</a>\n+\n+Mir27a Mir27a 2788.72629 -3.016676 0.1688167 2.036708e-71 2.843754e-69 21886 '..b'\n+\n+attr(,"contrasts")$group\n+\n+[1] contr.treatment\n+\n+R version 3.0.1 (2013-05-16)\n+\n+Platform: x86_64-unknown-linux-gnu (64-bit)\n+\n+locale:\n+\n+ [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8 LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8 LC_PAPER=C LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C \n+\n+attached base packages:\n+\n+ [1] parallel splines methods grid stats graphics grDevices utils datasets base \n+\n+other attached packages:\n+\n+ [1] RColorBrewer_1.0-5 DESeq2_1.0.18 RcppArmadillo_0.3.900.7 Rcpp_0.10.4 lattice_0.20-15 Biobase_2.20.1 GenomicRanges_1.12.4 IRanges_1.18.2 BiocGenerics_0.6.0 edgeR_3.2.4 limma_3.16.7 gplots_2.11.3 MASS_7.3-28 KernSmooth_2.23-10 caTools_1.14 gdata_2.13.2 gtools_3.0.0 stringr_0.6.2 \n+\n+loaded via a namespace (and not attached):\n+\n+ [1] annotate_1.38.0 AnnotationDbi_1.22.6 bitops_1.0-5 DBI_0.2-7 genefilter_1.42.0 locfit_1.5-9.1 RSQLite_0.11.4 stats4_3.0.1 survival_2.37-4 XML_3.98-1.1 xtable_1.7-1 \n+\n+\n+</pre>\n+\n+<div class="toolFormTitle">All output files available for downloading</div>\n+\n+<div><table class="colored" cellpadding="3" cellspacing="3"><tr><th>Output File Name (click to view)</th><th>Size</th></tr>\n+\n+<tr><td><a href="DESeq2.log">DESeq2.log</a></td><td>10.0 KB</td></tr>\n+<tr class="odd_row"><td><a href="DESeq2_MA_plot.pdf">DESeq2_MA_plot.pdf</a></td><td>14.7 KB</td></tr>\n+<tr><td><a href="DESeq2_PCA_plot.pdf">DESeq2_PCA_plot.pdf</a></td><td>4.9 KB</td></tr>\n+<tr class="odd_row"><td><a href="DESeq2_dispersion_estimates.pdf">DESeq2_dispersion_estimates.pdf</a></td><td>188.4 KB</td></tr>\n+<tr><td><a href="DESeq2_qqplot.pdf">DESeq2_qqplot.pdf</a></td><td>14.4 KB</td></tr>\n+<tr class="odd_row"><td><a href="DESeq2_sample_distance_plot.pdf">DESeq2_sample_distance_plot.pdf</a></td><td>9.5 KB</td></tr>\n+<tr><td><a href="DifferentialCounts.Rscript">DifferentialCounts.Rscript</a></td><td>27.1 KB</td></tr>\n+<tr class="odd_row"><td><a href="DifferentialCounts_error.log">DifferentialCounts_error.log</a></td><td>3.1 KB</td></tr>\n+<tr><td><a href="DifferentialCounts_runner.log">DifferentialCounts_runner.log</a></td><td>3.2 KB</td></tr>\n+<tr class="odd_row"><td><a href="Filtering_rowsum_bar_charts.pdf">Filtering_rowsum_bar_charts.pdf</a></td><td>6.3 KB</td></tr>\n+<tr><td><a href="VOOM.log">VOOM.log</a></td><td>10.1 KB</td></tr>\n+<tr class="odd_row"><td><a href="VOOM_mean_variance_plot.pdf">VOOM_mean_variance_plot.pdf</a></td><td>16.7 KB</td></tr>\n+<tr><td><a href="VOOM_qqplot.pdf">VOOM_qqplot.pdf</a></td><td>17.6 KB</td></tr>\n+<tr class="odd_row"><td><a href="Venn_significant_genes_overlap.pdf">Venn_significant_genes_overlap.pdf</a></td><td>9.7 KB</td></tr>\n+<tr><td><a href="edgeR.log">edgeR.log</a></td><td>13.1 KB</td></tr>\n+<tr class="odd_row"><td><a href="edgeR_BCV_vs_abundance.pdf">edgeR_BCV_vs_abundance.pdf</a></td><td>17.4 KB</td></tr>\n+<tr><td><a href="edgeR_GoodnessofFit.pdf">edgeR_GoodnessofFit.pdf</a></td><td>13.1 KB</td></tr>\n+<tr class="odd_row"><td><a href="edgeR_MDSplot.pdf">edgeR_MDSplot.pdf</a></td><td>4.9 KB</td></tr>\n+<tr><td><a href="edgeR_qqplot.pdf">edgeR_qqplot.pdf</a></td><td>15.2 KB</td></tr>\n+<tr class="odd_row"><td><a href="edgeR_raw_norm_counts_box.pdf">edgeR_raw_norm_counts_box.pdf</a></td><td>7.8 KB</td></tr>\n+<tr><td><a href="edgeR_smearplot.pdf">edgeR_smearplot.pdf</a></td><td>16.6 KB</td></tr>\n+<tr class="odd_row"><td><a href="edgeR_top_100_heatmap.pdf">edgeR_top_100_heatmap.pdf</a></td><td>11.3 KB</td></tr>\n+<tr><td><a href="sample_counts_histogram.pdf">sample_counts_histogram.pdf</a></td><td>11.0 KB</td></tr>\n+</table></div><br/>\n+</div></body></html>\n+\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/test-data/edgeRtest1out.xls --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/test-data/edgeRtest1out.xls Wed Aug 07 23:49:40 2013 -0400 |
| b |
| b"@@ -0,0 +1,1142 @@\n+ID\tlogFC\tAveExpr\tt\tP.Value\tadj.P.Val\tB\tNReads\tURL\n+Mir192\t6.94888256843679\t14.6763802609023\t42.7229535356942\t2.30119906424271e-16\t2.62566813230094e-13\t27.2664713266936\t2325567\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir192'>Mir192</a>\n+Mir208a\t-11.0150177152075\t3.93955375669227\t-23.2524066836307\t1.11893807599952e-12\t6.38354172357727e-10\t17.2086622097974\t4638\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir208a'>Mir208a</a>\n+Mir122a\t10.4261254701779\t8.16986409392255\t21.7229119192922\t2.85968233611017e-12\t1.08763251516723e-09\t17.760171141852\t90428\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir122a'>Mir122a</a>\n+Mir149\t-7.03046258655617\t6.31608073609863\t-20.8838348040628\t4.91549082404237e-12\t1.40214375755809e-09\t17.2776088871455\t6164\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir149'>Mir149</a>\n+Mir208b\t-12.4332279840446\t4.60762179736006\t-19.5924575126382\t1.17919871718875e-11\t2.69093147262473e-09\t15.6836663826186\t14756\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir208b'>Mir208b</a>\n+Mir10b\t-5.1309149063532\t12.2628671946242\t-18.2420234752943\t3.12499057505143e-11\t4.96397841614262e-09\t16.2215027882858\t197340\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir10b'>Mir10b</a>\n+Mir143hg\t-2.24922058313374\t16.2444825488726\t-18.0824813146443\t3.52173903971276e-11\t4.96397841614262e-09\t16.0266951625541\t1407364\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir143hg'>Mir143hg</a>\n+Mir143\t-2.25106712131643\t16.235859869169\t-18.0814805993441\t3.524391092512e-11\t4.96397841614262e-09\t16.0260836456534\t1399819\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir143'>Mir143</a>\n+Mir499\t-11.5675289490546\t3.78745976580796\t-17.9420857279689\t3.91549568319751e-11\t4.96397841614262e-09\t14.8217405828874\t6527\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir499'>Mir499</a>\n+Mir802\t9.15843445824816\t2.91576747878654\t17.3165224121399\t6.33861560587965e-11\t7.23236040630868e-09\t14.381577240531\t1514\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir802'>Mir802</a>\n+Mir3073\t8.42054159318439\t2.54571889776166\t16.7026571721381\t1.03306635740721e-10\t1.03604453339228e-08\t13.9858447292853\t904\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir3073'>Mir3073</a>\n+Mir148a\t2.63821345578617\t15.4435819751152\t16.5481882215215\t1.17118649515038e-10\t1.03604453339228e-08\t14.8147917664862\t1002397\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir148a'>Mir148a</a>\n+Mir101b\t3.76572195114225\t10.8508440499081\t16.5385659719288\t1.1804188373444e-10\t1.03604453339228e-08\t14.9000274171241\t59019\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir101b'>Mir101b</a>\n+Mir490\t-8.47437764634465\t3.75069567634692\t-16.2596504905533\t1.48481644820999e-10\t1.21012540529114e-08\t13.4246171016517\t1741\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir490'>Mir490</a>\n+Mir21\t2.93853744034991\t13.1642916950886\t15.3754036511693\t3.14833456057776e-10\t2.39483315574615e-08\t13.8676979022068\t229120\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir21'>Mir21</a>\n+Mir181c\t-3.74256009957124\t9.62955774646065\t-15.2423608550805\t3.53706264458683e-10\t2.52236779842098e-08\t13.8104046176901\t23605\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir181c'>Mir181c</a>\n+Mir204\t-7.68442507149438\t4.77517348536933\t-15.0334839919296\t4.2542677795722e-10\t2.85536443323052e-08\t12.8224274879526\t2601\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir204'>Mir204</a>\n+Mir23a\t-3.16576837850821\t8.78965917558611\t-14.6311785109623\t6.11068192724496e-10\t3.87349337721472e-08\t13.2691736804205\t10118\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir23a'>Mir23a</a>\n+Mir181d\t-3.63621106402109\t6.37132182424908\t-14.3170733565449\t8.15750840848868e-10\t4.89879847057136e-08\t12.9563328312209\t2139\t<a href='http://www"..b"805078\t-0.880373807283523\t-0.0497068478436261\t0.961050697355324\t0.975480839012736\t-6.26527518040501\t6\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Gm12191'>Gm12191</a>\n+Rprl3\t0.0408471478447264\t-0.798864220211061\t0.0488367850296659\t0.961731876147215\t0.975480839012736\t-6.25649782741468\t8\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Rprl3'>Rprl3</a>\n+H19\t-0.0415019911233814\t-0.880373807283523\t-0.0480992443304892\t0.962309326654761\t0.975480839012736\t-6.26535636348749\t6\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/H19'>H19</a>\n+Ppifos\t-0.045813233148843\t-0.325698143245111\t-0.047655434486338\t0.962656813959983\t0.975480839012736\t-6.21600758126971\t15\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Ppifos'>Ppifos</a>\n+Mirlet7a-2\t-0.0146726577509692\t3.37472927372453\t-0.0386745178686727\t0.969690141624003\t0.981735981892624\t-6.74139737131634\t158\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mirlet7a-2'>Mirlet7a-2</a>\n+9530082P21Rik\t-0.027891459987058\t-1.27661443246381\t-0.0346374807689275\t0.972852600944678\t0.983192929741255\t-6.29990631175915\t4\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/9530082P21Rik'>9530082P21Rik</a>\n+Mir1196\t-0.027891459987058\t-1.27661443246381\t-0.0346374807689275\t0.972852600944678\t0.983192929741255\t-6.29990631175915\t4\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir1196'>Mir1196</a>\n+Kcnk2\t-0.0253403588431765\t-0.835052547360434\t-0.031369255395874\t0.975413152136616\t0.984908324414052\t-6.26109829686273\t7\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Kcnk2'>Kcnk2</a>\n+A930011G23Rik\t-0.0241809579465951\t-0.00965077170076215\t-0.0291709235913898\t0.977135635463562\t0.985775207837245\t-6.2074206456237\t12\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/A930011G23Rik'>A930011G23Rik</a>\n+Mir3103\t0.0180714470554271\t-1.13917247326995\t0.0259355368025229\t0.979670906552206\t0.987459809519494\t-6.2920042186438\t4\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir3103'>Mir3103</a>\n+Snora75\t-0.0172327656019052\t-0.590132795422603\t-0.021476287065286\t0.983165572405378\t0.989793060148976\t-6.23767380603265\t10\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Snora75'>Snora75</a>\n+4930414L22Rik\t-0.0152743869054217\t-0.484133182103234\t-0.0207679670021376\t0.983720710086713\t0.989793060148976\t-6.22874423282067\t8\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/4930414L22Rik'>4930414L22Rik</a>\n+Mipep\t0.0164012673799433\t-0.280376883322022\t0.0179445082376201\t0.985933647271923\t0.991145631310365\t-6.21618933242714\t14\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mipep'>Mipep</a>\n+Ippk\t-0.0101933209515463\t0.0857377294202925\t-0.0128542290662295\t0.989923536727642\t0.99288598158411\t-6.20831119150974\t15\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Ippk'>Ippk</a>\n+Mir598\t-0.00787301950188535\t1.52736379718861\t-0.0127956250729132\t0.989969473858512\t0.99288598158411\t-6.3747989571524\t44\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir598'>Mir598</a>\n+1500017E21Rik\t0.0125149432592357\t0.202348454937975\t0.0124053255048405\t0.990275413709656\t0.99288598158411\t-6.21004071500431\t20\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/1500017E21Rik'>1500017E21Rik</a>\n+Map1lc3a\t0.00968300434227123\t0.00717248334519302\t0.0097742078067436\t0.992337878036726\t0.994080350166729\t-6.20806203375241\t21\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Map1lc3a'>Map1lc3a</a>\n+Trappc13\t-0.00465914834988075\t-0.880373807283523\t-0.00622703745231414\t0.995118499154886\t0.995991410119056\t-6.26653097741332\t6\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Trappc13'>Trappc13</a>\n+Mir1966\t-0.00246570556544304\t-0.590132795422603\t-0.00337044327478241\t0.997357828291427\t0.997357828291427\t-6.23790561933129\t8\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir1966'>Mir1966</a>\n" |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/test-data/gentestdata.sh --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/test-data/gentestdata.sh Wed Aug 07 23:49:40 2013 -0400 |
| b |
| @@ -0,0 +1,9 @@ +#!/bin/bash +# generate test data for rgGSEA +# ross lazarus June 2013 +# adjust gseajar_path ! +GSEAJAR_PATH=/home/rlazarus/galaxy-central/tool_dependency_dir/gsea_jar/2.0.12/fubar/rg_gsea_test/8e291f464aa0/jars/gsea2-2.0.12.jar +python ../rgGSEA.py --input_tab "gsea_test_DGE.xls" --adjpvalcol "5" --signcol "2" --idcol "1" --outhtml "gseatestout.html" --input_name "gsea_test" --setMax "500" --setMin "15" --nPerm "10" --plotTop "20" --gsea_jar "$GSEAJAR_PATH" --output_dir "gseatestout" --mode "Max_probe" +--title "GSEA test" --builtin_gmt "gseatestdata.gmt" + + |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/test-data/test_bams2mx.xls --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/test-data/test_bams2mx.xls Wed Aug 07 23:49:40 2013 -0400 |
| b |
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Zfp672\t0\t0\t0\t0\t0\t2\t0\t0\n+Zfp783\t0\t0\t0\t0\t0\t0\t0\t0\n+Zfp809\t7\t1\t0\t0\t0\t4\t2\t0\n+Zfp821\t0\t0\t0\t2\t2\t0\t0\t0\n+Zfp862\t4\t0\t0\t0\t0\t10\t2\t0\n+Zim3\t0\t0\t0\t0\t0\t0\t0\t0\n+Zmynd8\t3\t5\t4\t4\t3\t8\t2\t1\n+Znf41-ps\t0\t0\t0\t0\t0\t0\t0\t0\n+Zp4-ps\t0\t0\t0\t0\t0\t0\t0\t0\n+Zscan4a\t0\t0\t0\t0\t0\t0\t0\t0\n+Zxda\t0\t0\t0\t0\t0\t0\t0\t0\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c differential_count_models/tool_dependencies.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/differential_count_models/tool_dependencies.xml Wed Aug 07 23:49:40 2013 -0400 |
| b |
| @@ -0,0 +1,35 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="r3" version="3.0.1"> + <repository changeset_revision="6e89ec508745" name="package_r3" owner="fubar" prior_installation_required="True" toolshed="http://testtoolshed.g2.bx.psu.edu/" /> + </package>package_ghostscript_9_07 + <package name="ghostscript" version="9.07"> + <repository changeset_revision="10222a7db54c" name="package_ghostscript_9_07" owner="fubar" prior_installation_required="True" toolshed="http://testtoolshed.g2.bx.psu.edu/" /> + </package> + <package name="graphicsmagick" version="1.3.18"> + <repository changeset_revision="50d546dfd6b9" name="package_graphicsmagick_1_3" owner="iuc" prior_installation_required="True" toolshed="http://testtoolshed.g2.bx.psu.edu/" /> + </package> + <package name="biocbasics" version="2.12"> + <install version="1.0"> + <actions> + <action type="set_environment_for_install"> + <repository changeset_revision="6e89ec508745" name="package_r3" owner="fubar" toolshed="http://testtoolshed.g2.bx.psu.edu/"> + <package name="r3" version="3.0.1" /> + </repository> + </action> + <action type="make_directory">$INSTALL_DIR</action> + <action type="shell_command">echo "source('http://bioconductor.org/biocLite.R')" > $INSTALL_DIR/runme.R</action> + <action type="shell_command">echo "installme=c('edgeR','limma','DESeq','DESeq2')" >> $INSTALL_DIR/runme.R</action> + <action type="shell_command">echo "biocLite()" >> $INSTALL_DIR/runme.R</action> + <action type="shell_command">echo "biocLite(installme)" >> $INSTALL_DIR/runme.R</action> + <action type="shell_command">echo "install.packages(c('stringr','gplots'),dependencies=T,repos='http://cran.us.r-project.org')" >> $INSTALL_DIR/runme.R</action> + <action type="shell_command">echo "quit(save='no')" >> $INSTALL_DIR/runme.R</action> + <action type="shell_command"> export PATH=$PATH && export R_HOME=$R_HOME && export R_LIBS=$R_LIBS && R CMD BATCH $INSTALL_DIR/runme.R </action> + </actions> + </install> + <readme>Installs some basic bioc packages for the edgeR wrapper and dependencies graphicsmagick (replaces imagemagick) and ghostscript for compressing R's bloated pdfs + It's clunky but this is the most convenient way I could get anything installed into the package_r3 + Note we use cran at fred hutch since no fastest mirror thingy + </readme> + </package> +</tool_dependency> |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c rgToolFactory.py --- a/rgToolFactory.py Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| [ |
| b'@@ -1,631 +0,0 @@\n-# rgToolFactory.py\n-# see https://bitbucket.org/fubar/galaxytoolfactory/wiki/Home\n-# \n-# copyright ross lazarus (ross stop lazarus at gmail stop com) May 2012\n-# \n-# all rights reserved\n-# Licensed under the LGPL\n-# suggestions for improvement and bug fixes welcome at https://bitbucket.org/fubar/galaxytoolfactory/wiki/Home\n-#\n-# august 2013\n-# found a problem with GS if $TMP or $TEMP missing - now inject /tmp and warn\n-#\n-# july 2013\n-# added ability to combine images and individual log files into html output\n-# just make sure there\'s a log file foo.log and it will be output\n-# together with all images named like "foo_*.pdf\n-# otherwise old format for html\n-#\n-# January 2013\n-# problem pointed out by Carlos Borroto\n-# added escaping for <>$ - thought I did that ages ago...\n-#\n-# August 11 2012 \n-# changed to use shell=False and cl as a sequence\n-\n-# This is a Galaxy tool factory for simple scripts in python, R or whatever ails ye.\n-# It also serves as the wrapper for the new tool.\n-# \n-# you paste and run your script\n-# Only works for simple scripts that read one input from the history.\n-# Optionally can write one new history dataset,\n-# and optionally collect any number of outputs into links on an autogenerated HTML page.\n-\n-# DO NOT install on a public or important site - please.\n-\n-# installed generated tools are fine if the script is safe.\n-# They just run normally and their user cannot do anything unusually insecure\n-# but please, practice safe toolshed.\n-# Read the fucking code before you install any tool \n-# especially this one\n-\n-# After you get the script working on some test data, you can\n-# optionally generate a toolshed compatible gzip file\n-# containing your script safely wrapped as an ordinary Galaxy script in your local toolshed for\n-# safe and largely automated installation in a production Galaxy.\n-\n-# If you opt for an HTML output, you get all the script outputs arranged\n-# as a single Html history item - all output files are linked, thumbnails for all the pdfs.\n-# Ugly but really inexpensive.\n-# \n-# Patches appreciated please. \n-#\n-#\n-# long route to June 2012 product\n-# Behold the awesome power of Galaxy and the toolshed with the tool factory to bind them\n-# derived from an integrated script model \n-# called rgBaseScriptWrapper.py\n-# Note to the unwary:\n-# This tool allows arbitrary scripting on your Galaxy as the Galaxy user\n-# There is nothing stopping a malicious user doing whatever they choose\n-# Extremely dangerous!!\n-# Totally insecure. So, trusted users only\n-#\n-# preferred model is a developer using their throw away workstation instance - ie a private site.\n-# no real risk. The universe_wsgi.ini admin_users string is checked - only admin users are permitted to run this tool.\n-#\n-\n-import sys \n-import shutil \n-import subprocess \n-import os \n-import time \n-import tempfile \n-import optparse\n-import tarfile\n-import re\n-import shutil\n-import math\n-\n-progname = os.path.split(sys.argv[0])[1] \n-myversion = \'V000.2 June 2012\' \n-verbose = False \n-debug = False\n-toolFactoryURL = \'https://bitbucket.org/fubar/galaxytoolfactory\'\n-\n-def timenow():\n- """return current time as a string\n- """\n- return time.strftime(\'%d/%m/%Y %H:%M:%S\', time.localtime(time.time()))\n-\n-html_escape_table = {\n- "&": "&",\n- ">": ">",\n- "<": "<",\n- "$": "\\$"\n- }\n-\n-def html_escape(text):\n- """Produce entities within text."""\n- return "".join(html_escape_table.get(c,c) for c in text)\n-\n-def cmd_exists(cmd):\n- return subprocess.call("type " + cmd, shell=True, \n- stdout=subprocess.PIPE, stderr=subprocess.PIPE) == 0\n-\n-\n-class ScriptRunner:\n- """class is a wrapper for an arbitrary script\n- """\n-\n- def __init__(self,opts=None,treatbashSpecial=True):\n- """\n- cleanup inputs, setup some outputs\n- \n- """\n- self.useGM = cmd_exists(\'gm\')\n- self.useIM = cmd_exists(\'convert\')\n- self.useGS = cmd_exists(\'gs\')\n'..b'he display\n- else:\n- html.append(\'<div class="warningmessagelarge">### Error - %s returned no files - please confirm that parameters are sane</div>\' % self.opts.interpreter)\n- html.append(galhtmlpostfix)\n- htmlf = file(self.opts.output_html,\'w\')\n- htmlf.write(\'\\n\'.join(html))\n- htmlf.write(\'\\n\')\n- htmlf.close()\n- self.html = html\n-\n-\n- def run(self):\n- """\n- scripts must be small enough not to fill the pipe!\n- """\n- if self.treatbashSpecial and self.opts.interpreter in [\'bash\',\'sh\']:\n- retval = self.runBash()\n- else:\n- if self.opts.output_dir:\n- ste = open(self.elog,\'w\')\n- sto = open(self.tlog,\'w\')\n- sto.write(\'## Toolfactory generated command line = %s\\n\' % \' \'.join(self.cl))\n- sto.flush()\n- p = subprocess.Popen(self.cl,shell=False,stdout=sto,stderr=ste,stdin=subprocess.PIPE,cwd=self.opts.output_dir)\n- else:\n- p = subprocess.Popen(self.cl,shell=False,stdin=subprocess.PIPE)\n- p.stdin.write(self.script)\n- p.stdin.close()\n- retval = p.wait()\n- if self.opts.output_dir:\n- sto.close()\n- ste.close()\n- err = open(self.elog,\'r\').readlines()\n- if retval <> 0 and err: # problem\n- print >> sys.stderr,err\n- if self.opts.make_HTML:\n- self.makeHtml()\n- return retval\n-\n- def runBash(self):\n- """\n- cannot use - for bash so use self.sfile\n- """\n- if self.opts.output_dir:\n- s = \'## Toolfactory generated command line = %s\\n\' % \' \'.join(self.cl)\n- sto = open(self.tlog,\'w\')\n- sto.write(s)\n- sto.flush()\n- p = subprocess.Popen(self.cl,shell=False,stdout=sto,stderr=sto,cwd=self.opts.output_dir)\n- else:\n- p = subprocess.Popen(self.cl,shell=False) \n- retval = p.wait()\n- if self.opts.output_dir:\n- sto.close()\n- if self.opts.make_HTML:\n- self.makeHtml()\n- return retval\n- \n-\n-def main():\n- u = """\n- This is a Galaxy wrapper. It expects to be called by a special purpose tool.xml as:\n- <command interpreter="python">rgBaseScriptWrapper.py --script_path "$scriptPath" --tool_name "foo" --interpreter "Rscript"\n- </command>\n- """\n- op = optparse.OptionParser()\n- a = op.add_option\n- a(\'--script_path\',default=None)\n- a(\'--tool_name\',default=None)\n- a(\'--interpreter\',default=None)\n- a(\'--output_dir\',default=None)\n- a(\'--output_html\',default=None)\n- a(\'--input_tab\',default="None")\n- a(\'--output_tab\',default="None")\n- a(\'--user_email\',default=\'Unknown\')\n- a(\'--bad_user\',default=None)\n- a(\'--make_Tool\',default=None)\n- a(\'--make_HTML\',default=None)\n- a(\'--help_text\',default=None)\n- a(\'--tool_desc\',default=None)\n- a(\'--new_tool\',default=None)\n- a(\'--tool_version\',default=None)\n- opts, args = op.parse_args()\n- assert not opts.bad_user,\'UNAUTHORISED: %s is NOT authorized to use this tool until Galaxy admin adds %s to admin_users in universe_wsgi.ini\' % (opts.bad_user,opts.bad_user)\n- assert opts.tool_name,\'## Tool Factory expects a tool name - eg --tool_name=DESeq\'\n- assert opts.interpreter,\'## Tool Factory wrapper expects an interpreter - eg --interpreter=Rscript\'\n- assert os.path.isfile(opts.script_path),\'## Tool Factory wrapper expects a script path - eg --script_path=foo.R\'\n- if opts.output_dir:\n- try:\n- os.makedirs(opts.output_dir)\n- except:\n- pass\n- r = ScriptRunner(opts)\n- if opts.make_Tool:\n- retcode = r.makeTooltar()\n- else:\n- retcode = r.run()\n- os.unlink(r.sfile)\n- if retcode:\n- sys.exit(retcode) # indicate failure to job runner\n-\n-\n-if __name__ == "__main__":\n- main()\n-\n-\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c rgedgeRpaired.xml.camera --- a/rgedgeRpaired.xml.camera Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| b'@@ -1,1084 +0,0 @@\n-<tool id="rgDifferentialCount" name="Differential_Count" version="0.20">\n- <description>models using BioConductor packages</description>\n- <requirements>\n- <requirement type="package" version="2.12">biocbasics</requirement>\n- <requirement type="package" version="3.0.1">r3</requirement>\n- <requirement type="package" version="1.3.18">graphicsmagick</requirement>\n- <requirement type="package" version="9.07">ghostscript</requirement>\n- </requirements>\n- \n- <command interpreter="python">\n- rgToolFactory.py --script_path "$runme" --interpreter "Rscript" --tool_name "DifferentialCounts" \n- --output_dir "$html_file.files_path" --output_html "$html_file" --make_HTML "yes"\n- </command>\n- <inputs>\n- <param name="input1" type="data" format="tabular" label="Select an input matrix - rows are contigs, columns are counts for each sample"\n- help="Use the HTSeq based count matrix preparation tool to create these matrices from BAM/SAM files and a GTF file of genomic features"/>\n- <param name="title" type="text" value="Differential Counts" size="80" label="Title for job outputs" \n- help="Supply a meaningful name here to remind you what the outputs contain">\n- <sanitizer invalid_char="">\n- <valid initial="string.letters,string.digits"><add value="_" /> </valid>\n- </sanitizer>\n- </param>\n- <param name="treatment_name" type="text" value="Treatment" size="50" label="Treatment Name"/>\n- <param name="Treat_cols" label="Select columns containing treatment." type="data_column" data_ref="input1" numerical="True" \n- multiple="true" use_header_names="true" size="120" display="checkboxes">\n- <validator type="no_options" message="Please select at least one column."/>\n- </param>\n- <param name="control_name" type="text" value="Control" size="50" label="Control Name"/>\n- <param name="Control_cols" label="Select columns containing control." type="data_column" data_ref="input1" numerical="True" \n- multiple="true" use_header_names="true" size="120" display="checkboxes" optional="true">\n- </param>\n- <param name="subjectids" type="text" optional="true" size="120" value = ""\n- label="IF SUBJECTS NOT ALL INDEPENDENT! Enter comma separated strings to indicate sample labels for (eg) pairing - must be one for every column in input"\n- help="Leave blank if no pairing, but eg if data from sample id A99 is in columns 2,4 and id C21 is in 3,5 then enter \'A99,C21,A99,C21\'">\n- <sanitizer>\n- <valid initial="string.letters,string.digits"><add value="," /> </valid>\n- </sanitizer>\n- </param>\n- <param name="fQ" type="float" value="0.3" size="5" label="Non-differential contig count quantile threshold - zero to analyze all non-zero read count contigs"\n- help="May be a good or a bad idea depending on the biology and the question. EG 0.3 = sparsest 30% of contigs with at least one read are removed before analysis"/>\n- <param name="useNDF" type="boolean" truevalue="T" falsevalue="F" checked="false" size="1" \n- label="Non differential filter - remove contigs below a threshold (1 per million) for half or more samples"\n- help="May be a good or a bad idea depending on the biology and the question. This was the old default. Quantile based is available as an alternative"/>\n-\n- <conditional name="edgeR">\n- <param name="doedgeR" type="select" \n- label="Run this model using edgeR"\n- help="edgeR uses a negative binomial model and seems to be powerful, even with few replicates">\n- <option value="F">Do not run edgeR</option>\n- <option value="T" selected="true">Run edgeR</option>\n- </param>\n- <when value="T">\n- <param name="edgeR_priordf" type="integer" value="20" size="3" \n- label="prior.df for tagwise dispersion - lower value = more emphasis on each tag\'s variance. Replaces prior.n and prior.df = prior.n * residual.df"\n'..b'Preprint.pdf\n-\n-See Also\n-\n-A voom case study is given in the edgeR User\'s Guide.\n-\n-vooma is a similar function but for microarrays instead of RNA-seq.\n-\n-\n-***old rant on changes to Bioconductor package variable names between versions***\n-\n-The edgeR authors made a small cosmetic change in the name of one important variable (from p.value to PValue) \n-breaking this and all other code that assumed the old name for this variable, \n-between edgeR2.4.4 and 2.4.6 (the version for R 2.14 as at the time of writing). \n-This means that all code using edgeR is sensitive to the version. I think this was a very unwise thing \n-to do because it wasted hours of my time to track down and will similarly cost other edgeR users dearly\n-when their old scripts break. This tool currently now works with 2.4.6.\n-\n-**Note on prior.N**\n-\n-http://seqanswers.com/forums/showthread.php?t=5591 says:\n-\n-*prior.n*\n-\n-The value for prior.n determines the amount of smoothing of tagwise dispersions towards the common dispersion. \n-You can think of it as like a "weight" for the common value. (It is actually the weight for the common likelihood \n-in the weighted likelihood equation). The larger the value for prior.n, the more smoothing, i.e. the closer your \n-tagwise dispersion estimates will be to the common dispersion. If you use a prior.n of 1, then that gives the \n-common likelihood the weight of one observation.\n-\n-In answer to your question, it is a good thing to squeeze the tagwise dispersions towards a common value, \n-or else you will be using very unreliable estimates of the dispersion. I would not recommend using the value that \n-you obtained from estimateSmoothing()---this is far too small and would result in virtually no moderation \n-(squeezing) of the tagwise dispersions. How many samples do you have in your experiment? \n-What is the experimental design? If you have few samples (less than 6) then I would suggest a prior.n of at least 10. \n-If you have more samples, then the tagwise dispersion estimates will be more reliable, \n-so you could consider using a smaller prior.n, although I would hesitate to use a prior.n less than 5. \n-\n-\n-From Bioconductor Digest, Vol 118, Issue 5, Gordon writes:\n-\n-Dear Dorota,\n-\n-The important settings are prior.df and trend.\n-\n-prior.n and prior.df are related through prior.df = prior.n * residual.df,\n-and your experiment has residual.df = 36 - 12 = 24. So the old setting of\n-prior.n=10 is equivalent for your data to prior.df = 240, a very large\n-value. Going the other way, the new setting of prior.df=10 is equivalent\n-to prior.n=10/24.\n-\n-To recover old results with the current software you would use\n-\n- estimateTagwiseDisp(object, prior.df=240, trend="none")\n-\n-To get the new default from old software you would use\n-\n- estimateTagwiseDisp(object, prior.n=10/24, trend=TRUE)\n-\n-Actually the old trend method is equivalent to trend="loess" in the new\n-software. You should use plotBCV(object) to see whether a trend is\n-required.\n-\n-Note you could also use\n-\n- prior.n = getPriorN(object, prior.df=10)\n-\n-to map between prior.df and prior.n.\n-\n-----\n-\n-**Attributions**\n-\n-edgeR - edgeR_ \n-\n-VOOM/limma - limma_VOOM_ \n-\n-DESeq2 - DESeq2_ for details\n-\n-See above for Bioconductor package documentation for packages exposed in Galaxy by this tool and app store package.\n-\n-Galaxy_ (that\'s what you are using right now!) for gluing everything together \n-\n-Otherwise, all code and documentation comprising this tool was written by Ross Lazarus and is \n-licensed to you under the LGPL_ like other rgenetics artefacts\n-\n-.. _LGPL: http://www.gnu.org/copyleft/lesser.html\n-.. _HTSeq: http://www-huber.embl.de/users/anders/HTSeq/doc/index.html\n-.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html\n-.. _DESeq2: http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html\n-.. _limma_VOOM: http://www.bioconductor.org/packages/release/bioc/html/limma.html\n-.. _Galaxy: http://getgalaxy.org\n-</help>\n-\n-</tool>\n-\n-\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c rgedgeRpaired_nocamera.xml --- a/rgedgeRpaired_nocamera.xml Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| b'@@ -1,1072 +0,0 @@\n-<tool id="rgDifferentialCount" name="Differential_Count" version="0.20">\n- <description>models using BioConductor packages</description>\n- <requirements>\n- <requirement type="package" version="2.12">biocbasics</requirement>\n- <requirement type="package" version="3.0.1">r3</requirement>\n- <requirement type="package" version="1.3.18">graphicsmagick</requirement>\n- <requirement type="package" version="9.07">ghostscript</requirement>\n- </requirements>\n- \n- <command interpreter="python">\n- rgToolFactory.py --script_path "$runme" --interpreter "Rscript" --tool_name "DifferentialCounts" \n- --output_dir "$html_file.files_path" --output_html "$html_file" --make_HTML "yes"\n- </command>\n- <inputs>\n- <param name="input1" type="data" format="tabular" label="Select an input matrix - rows are contigs, columns are counts for each sample"\n- help="Use the HTSeq based count matrix preparation tool to create these matrices from BAM/SAM files and a GTF file of genomic features"/>\n- <param name="title" type="text" value="Differential Counts" size="80" label="Title for job outputs" \n- help="Supply a meaningful name here to remind you what the outputs contain">\n- <sanitizer invalid_char="">\n- <valid initial="string.letters,string.digits"><add value="_" /> </valid>\n- </sanitizer>\n- </param>\n- <param name="treatment_name" type="text" value="Treatment" size="50" label="Treatment Name"/>\n- <param name="Treat_cols" label="Select columns containing treatment." type="data_column" data_ref="input1" numerical="True" \n- multiple="true" use_header_names="true" size="120" display="checkboxes">\n- <validator type="no_options" message="Please select at least one column."/>\n- </param>\n- <param name="control_name" type="text" value="Control" size="50" label="Control Name"/>\n- <param name="Control_cols" label="Select columns containing control." type="data_column" data_ref="input1" numerical="True" \n- multiple="true" use_header_names="true" size="120" display="checkboxes" optional="true">\n- </param>\n- <param name="subjectids" type="text" optional="true" size="120" value = ""\n- label="IF SUBJECTS NOT ALL INDEPENDENT! Enter comma separated strings to indicate sample labels for (eg) pairing - must be one for every column in input"\n- help="Leave blank if no pairing, but eg if data from sample id A99 is in columns 2,4 and id C21 is in 3,5 then enter \'A99,C21,A99,C21\'">\n- <sanitizer>\n- <valid initial="string.letters,string.digits"><add value="," /> </valid>\n- </sanitizer>\n- </param>\n- <param name="fQ" type="float" value="0.3" size="5" label="Non-differential contig count quantile threshold - zero to analyze all non-zero read count contigs"\n- help="May be a good or a bad idea depending on the biology and the question. EG 0.3 = sparsest 30% of contigs with at least one read are removed before analysis"/>\n- <param name="useNDF" type="boolean" truevalue="T" falsevalue="F" checked="false" size="1" \n- label="Non differential filter - remove contigs below a threshold (1 per million) for half or more samples"\n- help="May be a good or a bad idea depending on the biology and the question. This was the old default. Quantile based is available as an alternative"/>\n-\n- <conditional name="edgeR">\n- <param name="doedgeR" type="select" \n- label="Run this model using edgeR"\n- help="edgeR uses a negative binomial model and seems to be powerful, even with few replicates">\n- <option value="F">Do not run edgeR</option>\n- <option value="T" selected="true">Run edgeR</option>\n- </param>\n- <when value="T">\n- <param name="edgeR_priordf" type="integer" value="20" size="3" \n- label="prior.df for tagwise dispersion - lower value = more emphasis on each tag\'s variance. Replaces prior.n and prior.df = prior.n * residual.df"\n'..b'Preprint.pdf\n-\n-See Also\n-\n-A voom case study is given in the edgeR User\'s Guide.\n-\n-vooma is a similar function but for microarrays instead of RNA-seq.\n-\n-\n-***old rant on changes to Bioconductor package variable names between versions***\n-\n-The edgeR authors made a small cosmetic change in the name of one important variable (from p.value to PValue) \n-breaking this and all other code that assumed the old name for this variable, \n-between edgeR2.4.4 and 2.4.6 (the version for R 2.14 as at the time of writing). \n-This means that all code using edgeR is sensitive to the version. I think this was a very unwise thing \n-to do because it wasted hours of my time to track down and will similarly cost other edgeR users dearly\n-when their old scripts break. This tool currently now works with 2.4.6.\n-\n-**Note on prior.N**\n-\n-http://seqanswers.com/forums/showthread.php?t=5591 says:\n-\n-*prior.n*\n-\n-The value for prior.n determines the amount of smoothing of tagwise dispersions towards the common dispersion. \n-You can think of it as like a "weight" for the common value. (It is actually the weight for the common likelihood \n-in the weighted likelihood equation). The larger the value for prior.n, the more smoothing, i.e. the closer your \n-tagwise dispersion estimates will be to the common dispersion. If you use a prior.n of 1, then that gives the \n-common likelihood the weight of one observation.\n-\n-In answer to your question, it is a good thing to squeeze the tagwise dispersions towards a common value, \n-or else you will be using very unreliable estimates of the dispersion. I would not recommend using the value that \n-you obtained from estimateSmoothing()---this is far too small and would result in virtually no moderation \n-(squeezing) of the tagwise dispersions. How many samples do you have in your experiment? \n-What is the experimental design? If you have few samples (less than 6) then I would suggest a prior.n of at least 10. \n-If you have more samples, then the tagwise dispersion estimates will be more reliable, \n-so you could consider using a smaller prior.n, although I would hesitate to use a prior.n less than 5. \n-\n-\n-From Bioconductor Digest, Vol 118, Issue 5, Gordon writes:\n-\n-Dear Dorota,\n-\n-The important settings are prior.df and trend.\n-\n-prior.n and prior.df are related through prior.df = prior.n * residual.df,\n-and your experiment has residual.df = 36 - 12 = 24. So the old setting of\n-prior.n=10 is equivalent for your data to prior.df = 240, a very large\n-value. Going the other way, the new setting of prior.df=10 is equivalent\n-to prior.n=10/24.\n-\n-To recover old results with the current software you would use\n-\n- estimateTagwiseDisp(object, prior.df=240, trend="none")\n-\n-To get the new default from old software you would use\n-\n- estimateTagwiseDisp(object, prior.n=10/24, trend=TRUE)\n-\n-Actually the old trend method is equivalent to trend="loess" in the new\n-software. You should use plotBCV(object) to see whether a trend is\n-required.\n-\n-Note you could also use\n-\n- prior.n = getPriorN(object, prior.df=10)\n-\n-to map between prior.df and prior.n.\n-\n-----\n-\n-**Attributions**\n-\n-edgeR - edgeR_ \n-\n-VOOM/limma - limma_VOOM_ \n-\n-DESeq2 - DESeq2_ for details\n-\n-See above for Bioconductor package documentation for packages exposed in Galaxy by this tool and app store package.\n-\n-Galaxy_ (that\'s what you are using right now!) for gluing everything together \n-\n-Otherwise, all code and documentation comprising this tool was written by Ross Lazarus and is \n-licensed to you under the LGPL_ like other rgenetics artefacts\n-\n-.. _LGPL: http://www.gnu.org/copyleft/lesser.html\n-.. _HTSeq: http://www-huber.embl.de/users/anders/HTSeq/doc/index.html\n-.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html\n-.. _DESeq2: http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html\n-.. _limma_VOOM: http://www.bioconductor.org/packages/release/bioc/html/limma.html\n-.. _Galaxy: http://getgalaxy.org\n-</help>\n-\n-</tool>\n-\n-\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c test-data/edgeRtest1out.html --- a/test-data/edgeRtest1out.html Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| [ |
| b'@@ -1,733 +0,0 @@\n-<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> \n- <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en"> \n- <head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> \n- <meta name="generator" content="Galaxy rgToolFactory.py tool output - see http://g2.trac.bx.psu.edu/" /> \n- <title></title> \n- <link rel="stylesheet" href="/static/style/base.css" type="text/css" /> \n- </head> \n- <body> \n- <div class="toolFormBody"> \n- \n-<div class="infomessage">Galaxy Tool "DifferentialCounts" run at 07/08/2013 15:46:55</div><br/>\n-<div class="toolFormTitle">DESeq2 images and outputs</div>\n-(Click on a thumbnail image to download the corresponding original PDF image)<br/>\n-<div><table class="simple" cellpadding="2" cellspacing="2">\n-<tr>\n-<td><a href="DESeq2_MA_plot.pdf"><img src="DESeq2_MA_plot.png" title="Click to download a PDF of DESeq2_MA_plot.pdf" hspace="5" width="400" \n- alt="Image called DESeq2_MA_plot.pdf"/></a></td>\n-\n-<td><a href="DESeq2_PCA_plot.pdf"><img src="DESeq2_PCA_plot.png" title="Click to download a PDF of DESeq2_PCA_plot.pdf" hspace="5" width="400" \n- alt="Image called DESeq2_PCA_plot.pdf"/></a></td>\n-\n-<td><a href="DESeq2_dispersion_estimates.pdf"><img src="DESeq2_dispersion_estimates.png" title="Click to download a PDF of DESeq2_dispersion_estimates.pdf" hspace="5" width="400" \n- alt="Image called DESeq2_dispersion_estimates.pdf"/></a></td>\n-</tr>\n-<tr>\n-<td><a href="DESeq2_qqplot.pdf"><img src="DESeq2_qqplot.png" title="Click to download a PDF of DESeq2_qqplot.pdf" hspace="5" width="400" \n- alt="Image called DESeq2_qqplot.pdf"/></a></td>\n-\n-<td><a href="DESeq2_sample_distance_plot.pdf"><img src="DESeq2_sample_distance_plot.png" title="Click to download a PDF of DESeq2_sample_distance_plot.pdf" hspace="5" width="400" \n- alt="Image called DESeq2_sample_distance_plot.pdf"/></a></td>\n-\n-<td> </td>\n-</tr></table></div>\n-\n-<div class="toolFormTitle">DESeq2 log output</div>\n-\n-<pre>\n-\n-# DESeq top 50\n-\n- Contig baseMean log2FoldChange lfcSE pvalue padj NReads URL\n-\n-Mir192 Mir192 271352.97636 6.965264 0.2150593 4.096936e-230 4.576278e-227 2325567 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir192\'>Mir192</a>\n-\n-Mir122a Mir122a 10112.31117 10.312083 0.3292695 2.649323e-215 1.479647e-212 90428 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir122a\'>Mir122a</a>\n-\n-Mir149 Mir149 810.35429 -6.911118 0.2341392 1.735537e-191 6.461982e-189 6164 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir149\'>Mir149</a>\n-\n-Mir23a Mir23a 1289.18043 -3.104086 0.1191688 1.424246e-149 3.977206e-147 10118 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir23a\'>Mir23a</a>\n-\n-Mir181d Mir181d 275.22797 -3.581172 0.1778187 3.329371e-90 7.437816e-88 2139 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir181d\'>Mir181d</a>\n-\n-Mir204 Mir204 347.57397 -7.284200 0.3771119 3.959336e-83 7.370965e-81 2601 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir204\'>Mir204</a>\n-\n-Mir23b Mir23b 2028.55377 -2.065110 0.1085802 1.182361e-80 1.886711e-78 16387 <a href=\'http://www.genecards.org/index.php?path=/Search/keyword/Mir23b\'>Mir23b</a>\n-\n-Mir27a Mir27a 2788.72629 -3.016676 0.1688167 2.036708e-71 2.843754e-69 21886 '..b'\n-\n-attr(,"contrasts")$group\n-\n-[1] contr.treatment\n-\n-R version 3.0.1 (2013-05-16)\n-\n-Platform: x86_64-unknown-linux-gnu (64-bit)\n-\n-locale:\n-\n- [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8 LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8 LC_PAPER=C LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C \n-\n-attached base packages:\n-\n- [1] parallel splines methods grid stats graphics grDevices utils datasets base \n-\n-other attached packages:\n-\n- [1] RColorBrewer_1.0-5 DESeq2_1.0.18 RcppArmadillo_0.3.900.7 Rcpp_0.10.4 lattice_0.20-15 Biobase_2.20.1 GenomicRanges_1.12.4 IRanges_1.18.2 BiocGenerics_0.6.0 edgeR_3.2.4 limma_3.16.7 gplots_2.11.3 MASS_7.3-28 KernSmooth_2.23-10 caTools_1.14 gdata_2.13.2 gtools_3.0.0 stringr_0.6.2 \n-\n-loaded via a namespace (and not attached):\n-\n- [1] annotate_1.38.0 AnnotationDbi_1.22.6 bitops_1.0-5 DBI_0.2-7 genefilter_1.42.0 locfit_1.5-9.1 RSQLite_0.11.4 stats4_3.0.1 survival_2.37-4 XML_3.98-1.1 xtable_1.7-1 \n-\n-\n-</pre>\n-\n-<div class="toolFormTitle">All output files available for downloading</div>\n-\n-<div><table class="colored" cellpadding="3" cellspacing="3"><tr><th>Output File Name (click to view)</th><th>Size</th></tr>\n-\n-<tr><td><a href="DESeq2.log">DESeq2.log</a></td><td>10.0 KB</td></tr>\n-<tr class="odd_row"><td><a href="DESeq2_MA_plot.pdf">DESeq2_MA_plot.pdf</a></td><td>14.7 KB</td></tr>\n-<tr><td><a href="DESeq2_PCA_plot.pdf">DESeq2_PCA_plot.pdf</a></td><td>4.9 KB</td></tr>\n-<tr class="odd_row"><td><a href="DESeq2_dispersion_estimates.pdf">DESeq2_dispersion_estimates.pdf</a></td><td>188.4 KB</td></tr>\n-<tr><td><a href="DESeq2_qqplot.pdf">DESeq2_qqplot.pdf</a></td><td>14.4 KB</td></tr>\n-<tr class="odd_row"><td><a href="DESeq2_sample_distance_plot.pdf">DESeq2_sample_distance_plot.pdf</a></td><td>9.5 KB</td></tr>\n-<tr><td><a href="DifferentialCounts.Rscript">DifferentialCounts.Rscript</a></td><td>27.1 KB</td></tr>\n-<tr class="odd_row"><td><a href="DifferentialCounts_error.log">DifferentialCounts_error.log</a></td><td>3.1 KB</td></tr>\n-<tr><td><a href="DifferentialCounts_runner.log">DifferentialCounts_runner.log</a></td><td>3.2 KB</td></tr>\n-<tr class="odd_row"><td><a href="Filtering_rowsum_bar_charts.pdf">Filtering_rowsum_bar_charts.pdf</a></td><td>6.3 KB</td></tr>\n-<tr><td><a href="VOOM.log">VOOM.log</a></td><td>10.1 KB</td></tr>\n-<tr class="odd_row"><td><a href="VOOM_mean_variance_plot.pdf">VOOM_mean_variance_plot.pdf</a></td><td>16.7 KB</td></tr>\n-<tr><td><a href="VOOM_qqplot.pdf">VOOM_qqplot.pdf</a></td><td>17.6 KB</td></tr>\n-<tr class="odd_row"><td><a href="Venn_significant_genes_overlap.pdf">Venn_significant_genes_overlap.pdf</a></td><td>9.7 KB</td></tr>\n-<tr><td><a href="edgeR.log">edgeR.log</a></td><td>13.1 KB</td></tr>\n-<tr class="odd_row"><td><a href="edgeR_BCV_vs_abundance.pdf">edgeR_BCV_vs_abundance.pdf</a></td><td>17.4 KB</td></tr>\n-<tr><td><a href="edgeR_GoodnessofFit.pdf">edgeR_GoodnessofFit.pdf</a></td><td>13.1 KB</td></tr>\n-<tr class="odd_row"><td><a href="edgeR_MDSplot.pdf">edgeR_MDSplot.pdf</a></td><td>4.9 KB</td></tr>\n-<tr><td><a href="edgeR_qqplot.pdf">edgeR_qqplot.pdf</a></td><td>15.2 KB</td></tr>\n-<tr class="odd_row"><td><a href="edgeR_raw_norm_counts_box.pdf">edgeR_raw_norm_counts_box.pdf</a></td><td>7.8 KB</td></tr>\n-<tr><td><a href="edgeR_smearplot.pdf">edgeR_smearplot.pdf</a></td><td>16.6 KB</td></tr>\n-<tr class="odd_row"><td><a href="edgeR_top_100_heatmap.pdf">edgeR_top_100_heatmap.pdf</a></td><td>11.3 KB</td></tr>\n-<tr><td><a href="sample_counts_histogram.pdf">sample_counts_histogram.pdf</a></td><td>11.0 KB</td></tr>\n-</table></div><br/>\n-</div></body></html>\n-\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c test-data/edgeRtest1out.xls --- a/test-data/edgeRtest1out.xls Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| b"@@ -1,1142 +0,0 @@\n-ID\tlogFC\tAveExpr\tt\tP.Value\tadj.P.Val\tB\tNReads\tURL\n-Mir192\t6.94888256843679\t14.6763802609023\t42.7229535356942\t2.30119906424271e-16\t2.62566813230094e-13\t27.2664713266936\t2325567\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir192'>Mir192</a>\n-Mir208a\t-11.0150177152075\t3.93955375669227\t-23.2524066836307\t1.11893807599952e-12\t6.38354172357727e-10\t17.2086622097974\t4638\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir208a'>Mir208a</a>\n-Mir122a\t10.4261254701779\t8.16986409392255\t21.7229119192922\t2.85968233611017e-12\t1.08763251516723e-09\t17.760171141852\t90428\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir122a'>Mir122a</a>\n-Mir149\t-7.03046258655617\t6.31608073609863\t-20.8838348040628\t4.91549082404237e-12\t1.40214375755809e-09\t17.2776088871455\t6164\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir149'>Mir149</a>\n-Mir208b\t-12.4332279840446\t4.60762179736006\t-19.5924575126382\t1.17919871718875e-11\t2.69093147262473e-09\t15.6836663826186\t14756\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir208b'>Mir208b</a>\n-Mir10b\t-5.1309149063532\t12.2628671946242\t-18.2420234752943\t3.12499057505143e-11\t4.96397841614262e-09\t16.2215027882858\t197340\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir10b'>Mir10b</a>\n-Mir143hg\t-2.24922058313374\t16.2444825488726\t-18.0824813146443\t3.52173903971276e-11\t4.96397841614262e-09\t16.0266951625541\t1407364\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir143hg'>Mir143hg</a>\n-Mir143\t-2.25106712131643\t16.235859869169\t-18.0814805993441\t3.524391092512e-11\t4.96397841614262e-09\t16.0260836456534\t1399819\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir143'>Mir143</a>\n-Mir499\t-11.5675289490546\t3.78745976580796\t-17.9420857279689\t3.91549568319751e-11\t4.96397841614262e-09\t14.8217405828874\t6527\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir499'>Mir499</a>\n-Mir802\t9.15843445824816\t2.91576747878654\t17.3165224121399\t6.33861560587965e-11\t7.23236040630868e-09\t14.381577240531\t1514\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir802'>Mir802</a>\n-Mir3073\t8.42054159318439\t2.54571889776166\t16.7026571721381\t1.03306635740721e-10\t1.03604453339228e-08\t13.9858447292853\t904\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir3073'>Mir3073</a>\n-Mir148a\t2.63821345578617\t15.4435819751152\t16.5481882215215\t1.17118649515038e-10\t1.03604453339228e-08\t14.8147917664862\t1002397\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir148a'>Mir148a</a>\n-Mir101b\t3.76572195114225\t10.8508440499081\t16.5385659719288\t1.1804188373444e-10\t1.03604453339228e-08\t14.9000274171241\t59019\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir101b'>Mir101b</a>\n-Mir490\t-8.47437764634465\t3.75069567634692\t-16.2596504905533\t1.48481644820999e-10\t1.21012540529114e-08\t13.4246171016517\t1741\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir490'>Mir490</a>\n-Mir21\t2.93853744034991\t13.1642916950886\t15.3754036511693\t3.14833456057776e-10\t2.39483315574615e-08\t13.8676979022068\t229120\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir21'>Mir21</a>\n-Mir181c\t-3.74256009957124\t9.62955774646065\t-15.2423608550805\t3.53706264458683e-10\t2.52236779842098e-08\t13.8104046176901\t23605\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir181c'>Mir181c</a>\n-Mir204\t-7.68442507149438\t4.77517348536933\t-15.0334839919296\t4.2542677795722e-10\t2.85536443323052e-08\t12.8224274879526\t2601\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir204'>Mir204</a>\n-Mir23a\t-3.16576837850821\t8.78965917558611\t-14.6311785109623\t6.11068192724496e-10\t3.87349337721472e-08\t13.2691736804205\t10118\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir23a'>Mir23a</a>\n-Mir181d\t-3.63621106402109\t6.37132182424908\t-14.3170733565449\t8.15750840848868e-10\t4.89879847057136e-08\t12.9563328312209\t2139\t<a href='http://www"..b"805078\t-0.880373807283523\t-0.0497068478436261\t0.961050697355324\t0.975480839012736\t-6.26527518040501\t6\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Gm12191'>Gm12191</a>\n-Rprl3\t0.0408471478447264\t-0.798864220211061\t0.0488367850296659\t0.961731876147215\t0.975480839012736\t-6.25649782741468\t8\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Rprl3'>Rprl3</a>\n-H19\t-0.0415019911233814\t-0.880373807283523\t-0.0480992443304892\t0.962309326654761\t0.975480839012736\t-6.26535636348749\t6\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/H19'>H19</a>\n-Ppifos\t-0.045813233148843\t-0.325698143245111\t-0.047655434486338\t0.962656813959983\t0.975480839012736\t-6.21600758126971\t15\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Ppifos'>Ppifos</a>\n-Mirlet7a-2\t-0.0146726577509692\t3.37472927372453\t-0.0386745178686727\t0.969690141624003\t0.981735981892624\t-6.74139737131634\t158\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mirlet7a-2'>Mirlet7a-2</a>\n-9530082P21Rik\t-0.027891459987058\t-1.27661443246381\t-0.0346374807689275\t0.972852600944678\t0.983192929741255\t-6.29990631175915\t4\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/9530082P21Rik'>9530082P21Rik</a>\n-Mir1196\t-0.027891459987058\t-1.27661443246381\t-0.0346374807689275\t0.972852600944678\t0.983192929741255\t-6.29990631175915\t4\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir1196'>Mir1196</a>\n-Kcnk2\t-0.0253403588431765\t-0.835052547360434\t-0.031369255395874\t0.975413152136616\t0.984908324414052\t-6.26109829686273\t7\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Kcnk2'>Kcnk2</a>\n-A930011G23Rik\t-0.0241809579465951\t-0.00965077170076215\t-0.0291709235913898\t0.977135635463562\t0.985775207837245\t-6.2074206456237\t12\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/A930011G23Rik'>A930011G23Rik</a>\n-Mir3103\t0.0180714470554271\t-1.13917247326995\t0.0259355368025229\t0.979670906552206\t0.987459809519494\t-6.2920042186438\t4\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir3103'>Mir3103</a>\n-Snora75\t-0.0172327656019052\t-0.590132795422603\t-0.021476287065286\t0.983165572405378\t0.989793060148976\t-6.23767380603265\t10\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Snora75'>Snora75</a>\n-4930414L22Rik\t-0.0152743869054217\t-0.484133182103234\t-0.0207679670021376\t0.983720710086713\t0.989793060148976\t-6.22874423282067\t8\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/4930414L22Rik'>4930414L22Rik</a>\n-Mipep\t0.0164012673799433\t-0.280376883322022\t0.0179445082376201\t0.985933647271923\t0.991145631310365\t-6.21618933242714\t14\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mipep'>Mipep</a>\n-Ippk\t-0.0101933209515463\t0.0857377294202925\t-0.0128542290662295\t0.989923536727642\t0.99288598158411\t-6.20831119150974\t15\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Ippk'>Ippk</a>\n-Mir598\t-0.00787301950188535\t1.52736379718861\t-0.0127956250729132\t0.989969473858512\t0.99288598158411\t-6.3747989571524\t44\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir598'>Mir598</a>\n-1500017E21Rik\t0.0125149432592357\t0.202348454937975\t0.0124053255048405\t0.990275413709656\t0.99288598158411\t-6.21004071500431\t20\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/1500017E21Rik'>1500017E21Rik</a>\n-Map1lc3a\t0.00968300434227123\t0.00717248334519302\t0.0097742078067436\t0.992337878036726\t0.994080350166729\t-6.20806203375241\t21\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Map1lc3a'>Map1lc3a</a>\n-Trappc13\t-0.00465914834988075\t-0.880373807283523\t-0.00622703745231414\t0.995118499154886\t0.995991410119056\t-6.26653097741332\t6\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Trappc13'>Trappc13</a>\n-Mir1966\t-0.00246570556544304\t-0.590132795422603\t-0.00337044327478241\t0.997357828291427\t0.997357828291427\t-6.23790561933129\t8\t<a href='http://www.genecards.org/index.php?path=/Search/keyword/Mir1966'>Mir1966</a>\n" |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c test-data/gentestdata.sh --- a/test-data/gentestdata.sh Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| @@ -1,9 +0,0 @@ -#!/bin/bash -# generate test data for rgGSEA -# ross lazarus June 2013 -# adjust gseajar_path ! -GSEAJAR_PATH=/home/rlazarus/galaxy-central/tool_dependency_dir/gsea_jar/2.0.12/fubar/rg_gsea_test/8e291f464aa0/jars/gsea2-2.0.12.jar -python ../rgGSEA.py --input_tab "gsea_test_DGE.xls" --adjpvalcol "5" --signcol "2" --idcol "1" --outhtml "gseatestout.html" --input_name "gsea_test" --setMax "500" --setMin "15" --nPerm "10" --plotTop "20" --gsea_jar "$GSEAJAR_PATH" --output_dir "gseatestout" --mode "Max_probe" ---title "GSEA test" --builtin_gmt "gseatestdata.gmt" - - |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c test-data/test_bams2mx.xls --- a/test-data/test_bams2mx.xls Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| b'@@ -1,3243 +0,0 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Zfp672\t0\t0\t0\t0\t0\t2\t0\t0\n-Zfp783\t0\t0\t0\t0\t0\t0\t0\t0\n-Zfp809\t7\t1\t0\t0\t0\t4\t2\t0\n-Zfp821\t0\t0\t0\t2\t2\t0\t0\t0\n-Zfp862\t4\t0\t0\t0\t0\t10\t2\t0\n-Zim3\t0\t0\t0\t0\t0\t0\t0\t0\n-Zmynd8\t3\t5\t4\t4\t3\t8\t2\t1\n-Znf41-ps\t0\t0\t0\t0\t0\t0\t0\t0\n-Zp4-ps\t0\t0\t0\t0\t0\t0\t0\t0\n-Zscan4a\t0\t0\t0\t0\t0\t0\t0\t0\n-Zxda\t0\t0\t0\t0\t0\t0\t0\t0\n' |
| b |
| diff -r c4ee2e69d691 -r ca87f891210c tool_dependencies.xml --- a/tool_dependencies.xml Wed Aug 07 02:41:40 2013 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
| b |
| @@ -1,35 +0,0 @@ -<?xml version="1.0"?> -<tool_dependency> - <package name="r3" version="3.0.1"> - <repository changeset_revision="6e89ec508745" name="package_r3" owner="fubar" prior_installation_required="True" toolshed="http://testtoolshed.g2.bx.psu.edu/" /> - </package>package_ghostscript_9_07 - <package name="ghostscript" version="9.07"> - <repository changeset_revision="10222a7db54c" name="package_ghostscript_9_07" owner="fubar" prior_installation_required="True" toolshed="http://testtoolshed.g2.bx.psu.edu/" /> - </package> - <package name="graphicsmagick" version="1.3.18"> - <repository changeset_revision="50d546dfd6b9" name="package_graphicsmagick_1_3" owner="iuc" prior_installation_required="True" toolshed="http://testtoolshed.g2.bx.psu.edu/" /> - </package> - <package name="biocbasics" version="2.12"> - <install version="1.0"> - <actions> - <action type="set_environment_for_install"> - <repository changeset_revision="6e89ec508745" name="package_r3" owner="fubar" toolshed="http://testtoolshed.g2.bx.psu.edu/"> - <package name="r3" version="3.0.1" /> - </repository> - </action> - <action type="make_directory">$INSTALL_DIR</action> - <action type="shell_command">echo "source('http://bioconductor.org/biocLite.R')" > $INSTALL_DIR/runme.R</action> - <action type="shell_command">echo "installme=c('edgeR','limma','DESeq','DESeq2')" >> $INSTALL_DIR/runme.R</action> - <action type="shell_command">echo "biocLite()" >> $INSTALL_DIR/runme.R</action> - <action type="shell_command">echo "biocLite(installme)" >> $INSTALL_DIR/runme.R</action> - <action type="shell_command">echo "install.packages(c('stringr','gplots'),dependencies=T,repos='http://cran.us.r-project.org')" >> $INSTALL_DIR/runme.R</action> - <action type="shell_command">echo "quit(save='no')" >> $INSTALL_DIR/runme.R</action> - <action type="shell_command"> export PATH=$PATH && export R_HOME=$R_HOME && export R_LIBS=$R_LIBS && R CMD BATCH $INSTALL_DIR/runme.R </action> - </actions> - </install> - <readme>Installs some basic bioc packages for the edgeR wrapper and dependencies graphicsmagick (replaces imagemagick) and ghostscript for compressing R's bloated pdfs - It's clunky but this is the most convenient way I could get anything installed into the package_r3 - Note we use cran at fred hutch since no fastest mirror thingy - </readme> - </package> -</tool_dependency> |