def addPickleGenomeRBDictJob(self, workflow, executable=None, \
outputF=None, genePadding=None, tax_id=3702,\
parentJobLs=[], job_max_memory=100, extraDependentInputLs=[], \
transferOutput=False, **keywords):
"""
2012.3.22
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-v", self.genome_drivername, "-z", self.genome_hostname, "-d", self.genome_dbname, \
"-u", self.genome_db_user, "-p", self.genome_db_passwd,\
"--genePadding=%s"%(genePadding), "--tax_id=%s"%(tax_id), "-o", outputF)
if self.genome_schema:
job.addArguments("--schema=%s" % self.genome_schema)
job.uses(outputF,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputF
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
workflow.addJob(job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
return job
def addOutputLociIDOfResultPeakInHDF5Job(self, workflow, executable=None, peak_id=None, outputFile=None,\
parentJobLs=[], extraDependentInputLs=[], transferOutput=True, extraArguments=None, \
job_max_memory=10, **keywords):
"""
2012.3.10
-i 59444 -u yh -z banyan -o /tmp/peak_59444.h5
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-v", self.drivername, "-z", self.hostname, "-d", self.dbname, \
"-u", self.db_user, "-p", self.db_passwd,\
"-i", repr(int(peak_id)), "-o", outputFile)
if extraArguments:
job.addArguments(extraArguments)
job.uses(outputFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addSmartpcaJob(
self,
workflow,
executable=None,
smartpcaParameterFile=None,
parentJobLs=[],
extraDependentInputLs=[],
transferOutput=True,
extraArguments=None,
outputFileList=[],
job_max_memory=100,
**keywords
):
"""
2012.3.1
"""
job = Job(namespace=workflow.namespace, name=executable.name, version=workflow.version)
job.addArguments("-p", smartpcaParameterFile)
job.uses(smartpcaParameterFile, transfer=True, register=True, link=Link.INPUT)
if extraArguments:
job.addArguments(extraArguments)
for outputF in outputFileList:
if outputF:
job.uses(outputF, transfer=transferOutput, register=True, link=Link.OUTPUT)
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addConvertSNPData2HDF5Job(self, workflow, executable=None, inputFile=None, outputFile=None, min_MAF=None, \
parentJobLs=[], extraDependentInputLs=[], transferOutput=True, extraArguments=None, \
job_max_memory=100, **keywords):
"""
2012.3.2
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments('-i', inputFile, '-o', outputFile,
'-n %s' % (min_MAF))
job.uses(inputFile, transfer=True, register=True, link=Link.INPUT)
if extraArguments:
job.addArguments(extraArguments)
job.uses(outputFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addDrawManhattanPlotForLDInHDF5Job(self, workflow, executable=None, correlationFile=None, peak_id=None, \
datasetName=None, outputFile=None,\
outputFnamePrefix=None, parentJobLs=[], extraDependentInputLs=[], transferOutput=True, extraArguments=None, \
job_max_memory=10, **keywords):
"""
2012.3.10
DrawManhattanPlotForLDInHDF5.py -w secret -i /tmp/output.2.h5 -l 59444 -N correlation
-O /tmp/gw_LD_pattern_between_snp_and_peak_59444 -u yh -p secret
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-v", self.drivername, "-z", self.hostname, "-d", self.dbname, \
"-u", self.db_user, "-p", self.db_passwd, "-w", self.genome_db_passwd,\
"-l %s"%(peak_id),"-N", datasetName, "-i", correlationFile, "-O", outputFnamePrefix)
if extraArguments:
job.addArguments(extraArguments)
job.uses(correlationFile,
transfer=True,
register=True,
link=Link.INPUT)
job.uses(outputFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addCalculateColCorBetweenTwoHDF5Job(self, workflow, executable=None, inputFile1=None, inputFile2=None, outputFile=None, \
i1_start=None, i1_stop=None, i2_start=None, i2_stop=None, min_cor=None, \
parentJobLs=[], extraDependentInputLs=[], transferOutput=True, extraArguments=None, \
job_max_memory=100, **keywords):
"""
2012.3.2
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments('-o', outputFile,'-i', inputFile1, '-j', inputFile2, '-s %s'%i1_start, '-t %s'%i1_stop, \
'-u %s'%i2_start, '-v %s'%i2_stop, '-c %s'%min_cor)
job.uses(inputFile1, transfer=True, register=True, link=Link.INPUT)
job.uses(inputFile2, transfer=True, register=True, link=Link.INPUT)
if extraArguments:
job.addArguments(extraArguments)
job.uses(outputFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addPickleSNPInfoJob(self, workflow, executable=None, \
outputF=None, call_method_id=None, \
parentJobLs=[], job_max_memory=100, extraDependentInputLs=[], \
transferOutput=False, **keywords):
"""
2012.3.22
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-v", self.drivername, "-z", self.hostname, "-d", self.dbname, \
"-u", self.db_user, "-p", self.db_passwd, \
"--call_method_id=%s"%(call_method_id), "-F", outputF)
job.uses(outputF,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputF
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
workflow.addJob(job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
return job
def addGWASPeakOverlapJob(self, workflow, executable=None, \
result1_id=None, result2_id=None, association1_peak_type_id=None, \
association2_peak_type_id=None, peak_padding=None, outputF=None, \
commit=0, results_directory=None, logFile=None, \
parentJobLs=[], job_max_memory=100, walltime = 60, \
extraDependentInputLs=[], \
transferOutput=False, **keywords):
"""
2012.2.22
walltime is in minutes (max time allowed on hoffman2 is 24 hours).
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
#apply int because result1_id is of long int. and casting "434L" to integer will raise exception
job.addArguments("-v", self.drivername, "-z", self.hostname, "-d", self.dbname, \
"-u", self.db_user, "-p", self.db_passwd,\
"-i", repr(int(result1_id)), "-j", repr(int(result2_id)), \
"-x", repr(association1_peak_type_id), "-y", repr(association2_peak_type_id), \
"-e", repr(peak_padding), "-o", outputF)
job.uses(outputF,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
if commit:
job.addArguments("-c")
if results_directory:
job.addArguments(
"-t",
results_directory,
)
if self.schema:
job.addArguments(
"-k",
self.schema,
)
if logFile:
job.addArguments("--logFilename=%s" % (logFile.name))
job.uses(logFile,
transfer=transferOutput,
register=transferOutput,
link=Link.OUTPUT)
job.output = logFile
workflow.addJob(job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
yh_pegasus.setJobProperRequirement(job,
job_max_memory=job_max_memory,
walltime=walltime)
return job
def addPutReadBaseCountIntoDBJob(
self,
workflow,
executable=None,
inputFileLs=[],
logFile=None,
commit=False,
parentJobLs=[],
extraDependentInputLs=[],
transferOutput=True,
extraArguments=None,
job_max_memory=10,
sshDBTunnel=1,
**keywords
):
"""
2012.5.3
add argument sshDBTunnel
2012.3.14
"""
job = Job(namespace=workflow.namespace, name=executable.name, version=workflow.version)
job.addArguments(
"--drivername",
self.drivername,
"--hostname",
self.hostname,
"--dbname",
self.dbname,
"--db_user",
self.db_user,
"--db_passwd",
self.db_passwd,
"--logFilename",
logFile,
)
if extraArguments:
job.addArguments(extraArguments)
if commit:
job.addArguments("--commit")
for inputFile in inputFileLs:
job.addArguments(inputFile)
job.uses(inputFile, transfer=True, register=True, link=Link.INPUT)
job.uses(logFile, transfer=transferOutput, register=True, link=Link.OUTPUT)
job.output = logFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory, sshDBTunnel=sshDBTunnel)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addConvertVCF2EigenStratJob(
self,
workflow,
executable=None,
inputF=None,
outputFnamePrefix=None,
missingCallAsRefBase=None,
parentJobLs=[],
extraDependentInputLs=[],
transferOutput=True,
extraArguments=None,
job_max_memory=100,
**keywords
):
"""
2012.9.11 add argument missingCallAsRefBase
2012.3.1
"""
job = Job(namespace=workflow.namespace, name=executable.name, version=workflow.version)
job.addArguments("-i", inputF, "-O", outputFnamePrefix)
if missingCallAsRefBase:
job.addArguments("--missingCallAsRefBase")
if extraArguments:
job.addArguments(extraArguments)
job.uses(inputF, transfer=True, register=True, link=Link.INPUT)
genoOutputF = File("%s.geno" % (outputFnamePrefix))
locusOutputF = File("%s.snp" % (outputFnamePrefix))
indOutputF = File("%s.ind" % (outputFnamePrefix))
outputFLs = [genoOutputF, locusOutputF, indOutputF]
for outputF in outputFLs:
job.uses(outputF, transfer=transferOutput, register=True, link=Link.OUTPUT)
job.genoOutputF = genoOutputF
job.indOutputF = indOutputF
job.locusOutputF = locusOutputF
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
if parentJobLs:
for parentJob in parentJobLs:
if parentJob:
workflow.depends(parent=parentJob, child=job)
if extraDependentInputLs:
for input in extraDependentInputLs:
if input:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addPlotPeakOverlapJob(self, workflow, executable=None, \
outputFnamePrefix=None, \
parentJobLs=[], job_max_memory=100, walltime = 60, \
extraDependentInputLs=[], \
transferOutput=False, **keywords):
"""
2012.2.22
walltime is in minutes (max time allowed on hoffman2 is 24 hours).
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-o", outputFnamePrefix)
job.uses(File("%s_hist_of_fraction_of_association1_peaks_in_result2.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_hist_of_fraction_of_association2_peaks_in_result1.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_hist_of_fraction_of_recurrent_peaks_in_combined.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_no_of_peaks_result1_vs_result2.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_result1_no_of_peak_vs_fraction.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_result2_no_of_peak_vs_fraction.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_1_fraction_in2_vs_2_fraction_in1.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
job.uses(File("%s_combined_no_of_peak_vs_fraction.png"%outputFnamePrefix), \
transfer=True, register=True, link=Link.OUTPUT)
workflow.addJob(job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
yh_pegasus.setJobProperRequirement(job,
job_max_memory=job_max_memory,
walltime=walltime)
return job
def addOutputMultiGWASOverlapPeakSpanJob(self, workflow, executable=None, \
outputF=None, peakPadding=None,list_type_id_list=None, result_id_peak_type_id_ls=None,\
genePadding=None, tax_id=3702, genomeRBDictPickleFile=None, \
parentJobLs=[], job_max_memory=100, extraDependentInputLs=[], \
transferOutput=False, **keywords):
"""
2012.3.22
argument list_type_id_list is in string format. "129,137"
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-v", self.drivername, "-z", self.hostname, "-d", self.dbname, \
"-u", self.db_user, "-p", self.db_passwd, \
"--genome_drivername=%s"%self.genome_drivername, "--genome_hostname=%s"%self.genome_hostname, \
"--genome_dbname=%s"%self.genome_dbname, \
"--genome_db_user=%s"%self.genome_db_user, "--genome_schema=%s"%self.genome_schema, \
"--genome_db_passwd=%s"%self.genome_db_passwd,\
"--peakPadding=%s"%(peakPadding), \
"--result_id_peak_type_id_ls=%s"%(result_id_peak_type_id_ls), \
"--genePadding=%s"%(genePadding), \
"--tax_id=%s"%(tax_id), "-o", outputF)
if list_type_id_list:
job.addArguments("--list_type_id_list=%s" % (list_type_id_list))
if genomeRBDictPickleFile:
job.addArguments("-m", genomeRBDictPickleFile)
job.uses(genomeRBDictPickleFile,
transfer=True,
register=True,
link=Link.INPUT)
job.uses(outputF,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputF
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
workflow.addJob(job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
return job
def addFindMaxLDBetweenPeakAndEachLocusJob(self, workflow, executable=None, correlationFile=None, peakLociH5File=None, \
outputFile=None, row_start=None, row_stop=None, \
parentJobLs=[], extraDependentInputLs=[], transferOutput=True, extraArguments=None, \
job_max_memory=100, **keywords):
"""
2012.3.10
FindMaxLDBetweenPeakAndEachLocus -j /tmp/peak_59444.h5
-s 0 -t 1000
-i /Network/Data/250k/tmp-yh/pegasus/LD_between_call_32_and_80.2012.3.9T2005/LD/cor_i1_0_4999_i2_0_4999.h5
-o /tmp/output.3.h5
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-i", correlationFile, "-j", peakLociH5File, "-o",
outputFile)
if row_start is not None:
job.addArguments("-s %s" % (row_start))
if row_stop is not None:
job.addArguments("-t %s" % (row_stop))
if extraArguments:
job.addArguments(extraArguments)
job.uses(peakLociH5File,
transfer=False,
register=True,
link=Link.INPUT)
job.uses(correlationFile,
transfer=True,
register=True,
link=Link.INPUT)
job.uses(outputFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = outputFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addSplitFastaFileJob(self, executable=None, inputFile=None, outputFnamePrefix=None, \
noOfSequencesPerSplitFile=1000, filenameSuffix="", noOfTotalSequences=1000000,\
parentJobLs=[], extraDependentInputLs=[], transferOutput=False, \
extraArguments=None, job_max_memory=500, **keywords):
"""
2012.5.24
"""
job = Job(namespace=self.namespace,
name=executable.name,
version=self.version)
noOfSplitFiles = int(
math.ceil(noOfTotalSequences / float(noOfSequencesPerSplitFile)))
suffixLength = len(repr(noOfSplitFiles))
job.addArguments("-i", inputFile, "--noOfSequences %s"%(noOfSequencesPerSplitFile), \
"--outputFnamePrefix", outputFnamePrefix, '--filenameSuffix %s'%(filenameSuffix), '--suffixLength %s'%(suffixLength))
if extraArguments:
job.addArguments(extraArguments)
job.uses(inputFile, transfer=True, register=True, link=Link.INPUT)
job.outputList = []
for i in xrange(noOfSplitFiles): #start from 0
splitFname = utils.comeUpSplitFilename(outputFnamePrefix=outputFnamePrefix, suffixLength=suffixLength, fileOrder=i,\
filenameSuffix=filenameSuffix)
splitFile = File(splitFname)
job.outputList.append(splitFile)
job.uses(splitFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
self.addJob(job)
for parentJob in parentJobLs:
if parentJob:
self.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
if input:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addCountFastqReadBaseCountJob(
self,
workflow,
executable=None,
inputFile=None,
outputFile=None,
isq_id=None,
isqf_id=None,
parentJobLs=[],
extraDependentInputLs=[],
transferOutput=True,
extraArguments=None,
job_max_memory=100,
**keywords
):
"""
2012.3.14
"""
job = Job(namespace=workflow.namespace, name=executable.name, version=workflow.version)
job.addArguments("--inputFname", inputFile, "--outputFname", outputFile)
if isq_id:
job.addArguments("--isq_id %s" % (isq_id))
if isqf_id:
job.addArguments("--isqf_id %s" % (isqf_id))
if extraArguments:
job.addArguments(extraArguments)
job.uses(inputFile, transfer=True, register=True, link=Link.INPUT)
job.uses(outputFile, transfer=transferOutput, register=True, link=Link.OUTPUT)
job.output = outputFile
workflow.addJob(job)
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
return job
def addAddRG2BamJobsAsNeeded(self, workflow=None, alignmentDataLs=None, site_handler=None, input_site_handler=None, \
addOrReplaceReadGroupsJava=None, AddOrReplaceReadGroupsJar=None, \
BuildBamIndexFilesJava=None, BuildBamIndexJar=None, \
mv=None, \
data_dir=None, tmpDir="/tmp", **keywords):
"""
2012.4.5
fix some bugs here
2011-9-15
add a read group only when the alignment doesn't have it according to db record
DBVervet.pokeBamReadGroupPresence() from misc.py helps to fill in db records if it's unclear.
2011-9-14
The read-group adding jobs will have a "move" part that overwrites the original bam&bai if site_handler and input_site_handler is same.
For those alignment files that don't need to. It doesn't matter. pegasus will transfer/symlink them.
"""
sys.stderr.write(
"Adding add-read-group2BAM jobs for %s alignments if read group is not detected ..."
% (len(alignmentDataLs)))
if workflow is None:
workflow = self
job_max_memory = 3500 #in MB
javaMemRequirement = "-Xms128m -Xmx%sm" % job_max_memory
indexJobMaxMem = 2500
addRG2BamDir = None
addRG2BamDirJob = None
no_of_rg_jobs = 0
returnData = []
for alignmentData in alignmentDataLs:
alignment = alignmentData.alignment
parentJobLs = alignmentData.jobLs
bamF = alignmentData.bamF
baiF = alignmentData.baiF
if alignment.read_group_added != 1:
if addRG2BamDir is None:
addRG2BamDir = "addRG2Bam"
addRG2BamDirJob = self.addMkDirJob(outputDir=addRG2BamDir)
# add RG to this bam
sequencer = alignment.individual_sequence.sequencer
#read_group = '%s_%s_%s_%s_vs_%s'%(alignment.id, alignment.ind_seq_id, alignment.individual_sequence.individual.code, \
# sequencer, alignment.ref_ind_seq_id)
read_group = alignment.getReadGroup() ##2011-11-02
if sequencer == '454':
platform_id = 'LS454'
elif sequencer == 'GA':
platform_id = 'ILLUMINA'
else:
platform_id = 'ILLUMINA'
# the add-read-group job
#addRGJob = Job(namespace=namespace, name=addRGExecutable.name, version=version)
addRGJob = Job(namespace=workflow.namespace,
name=addOrReplaceReadGroupsJava.name,
version=workflow.version)
outputRGSAM = File(
os.path.join(addRG2BamDir,
os.path.basename(alignment.path)))
addRGJob.addArguments(javaMemRequirement, '-jar', AddOrReplaceReadGroupsJar, \
"INPUT=", bamF,\
'RGID=%s'%(read_group), 'RGLB=%s'%(platform_id), 'RGPL=%s'%(platform_id), \
'RGPU=%s'%(read_group), 'RGSM=%s'%(read_group),\
'OUTPUT=', outputRGSAM, 'SORT_ORDER=coordinate', "VALIDATION_STRINGENCY=LENIENT")
#(adding the SORT_ORDER doesn't do sorting but it marks the header as sorted so that BuildBamIndexJar won't fail.)
self.addJobUse(addRGJob,
file=AddOrReplaceReadGroupsJar,
transfer=True,
register=True,
link=Link.INPUT)
if tmpDir:
addRGJob.addArguments("TMP_DIR=%s" % tmpDir)
addRGJob.uses(bamF,
transfer=True,
register=True,
link=Link.INPUT)
addRGJob.uses(baiF,
transfer=True,
register=True,
link=Link.INPUT)
addRGJob.uses(outputRGSAM,
transfer=True,
register=True,
link=Link.OUTPUT)
yh_pegasus.setJobProperRequirement(
addRGJob, job_max_memory=job_max_memory)
for parentJob in parentJobLs:
if parentJob:
workflow.depends(parent=parentJob, child=addRGJob)
workflow.addJob(addRGJob)
index_sam_job = self.addBAMIndexJob(workflow, BuildBamIndexFilesJava=workflow.BuildBamIndexFilesJava, BuildBamIndexJar=workflow.BuildBamIndexJar, \
inputBamF=outputRGSAM, parentJobLs=[addRGJob], transferOutput=True, javaMaxMemory=2000)
newAlignmentData = PassingData(alignment=alignment)
newAlignmentData.jobLs = [index_sam_job, addRGJob]
newAlignmentData.bamF = index_sam_job.bamFile
newAlignmentData.baiF = index_sam_job.baiFile
"""
# add the index job to the bamF (needs to be re-indexed)
index_sam_job = Job(namespace=namespace, name=BuildBamIndexFilesJava.name, version=version)
if input_site_handler==site_handler: #on the same site. overwrite the original file without RG
mvJob = Job(namespace=namespace, name=mv.name, version=version)
mvJob.addArguments(outputRGSAM, inputFname) #watch, it's inputFname, not input. input is in relative path.
#samToBamJob.uses(outputRG, transfer=False, register=True, link=Link.OUTPUT) #don't register it here
workflow.addJob(mvJob)
workflow.depends(parent=addRGJob, child=mvJob)
bai_output = File('%s.bai'%inputFname) #in absolute path, don't register it to the job
else:
##on different site, input for index should be outputRGSAM and register it as well
mvJob = addRGJob
bamF = outputRGSAM
addRGJob.uses(outputRGSAM, transfer=True, register=True, link=Link.OUTPUT)
bai_output = File('%s.bai'%outputRGSAMFname)
index_sam_job.uses(bai_output, transfer=True, register=False, link=Link.OUTPUT)
index_sam_job
yh_pegasus.setJobProperRequirement(index_sam_job, job_max_memory=indexJobMaxMem)
workflow.addJob(index_sam_job)
workflow.depends(parent=mvJob, child=index_sam_job)
alignmentId2RGJobDataLs[alignment.id]= [index_sam_job, inputFile, bai_output]
"""
no_of_rg_jobs += 1
else:
newAlignmentData = alignmentData
returnData.append(newAlignmentData)
sys.stderr.write(" %s alignments need read-group addition. Done\n" %
(no_of_rg_jobs))
return returnData
def addDrawSNPRegionJob(self, workflow, executable=None, \
inputF=None, call_method_id=None, snpMatrixFile=None, phenotypeFile=None, output_dir=None,\
results_directory=None,analysis_method_id_ls=None, geneAnnotationPickleFile=None,\
list_type_id_list=None, snp_matrix_data_type=1, exclude_accessions_with_NA_phenotype=0,\
snpInfoPickleFile=None, label_gene=1, min_MAF=0.1, min_distance=20000,\
logFile=None,\
parentJobLs=[], job_max_memory=2000, extraDependentInputLs=[], \
transferOutput=False, **keywords):
"""
2012.3.22
argument analysis_method_id_ls, list_type_id_list are in string format. "129,137"
DrawSNPRegion.py -I /Network/Data/250k/db/dataset/call_method_80.tsv -N /Network/Data/250k/tmp-yh/phenotype/phenotype.tsv
-l 129 -o /Network/Data/250k/tmp-yh/snp_region -j /Network/Data/250k/tmp-yh/at_gene_model_pickelf
-e 80 -u yh -s -a 1,32 -z banyan -u yh
"""
job = Job(namespace=workflow.namespace,
name=executable.name,
version=workflow.version)
job.addArguments("-v", self.drivername, "-z", self.hostname, "-d", self.dbname, \
"-u", self.db_user, "-p", self.db_passwd, \
"-i", inputF,\
"--call_method_id=%s"%(call_method_id), \
"-I", snpMatrixFile, \
"-N", phenotypeFile, "--output_dir=%s"%(output_dir), \
"--analysis_method_id_ls=%s"%(analysis_method_id_ls),\
"-j", geneAnnotationPickleFile, "--list_type_id_list=%s"%(list_type_id_list), \
"--snp_matrix_data_type=%s"%(snp_matrix_data_type), \
"--min_MAF=%s"%(min_MAF), "--min_distance=%s"%(min_distance),
)
job.uses(inputF, transfer=True, register=True, link=Link.INPUT)
job.uses(snpMatrixFile, transfer=True, register=True, link=Link.INPUT)
job.uses(phenotypeFile, transfer=True, register=True, link=Link.INPUT)
job.uses(geneAnnotationPickleFile,
transfer=True,
register=True,
link=Link.INPUT)
if exclude_accessions_with_NA_phenotype:
job.addArguments("--exclude_accessions_with_NA_phenotype")
if label_gene:
job.addArguments("--label_gene")
if results_directory:
job.addArguments("--results_directory=%s" % (results_directory))
if snpInfoPickleFile:
job.addArguments("-F", snpInfoPickleFile)
job.uses(snpInfoPickleFile,
transfer=True,
register=True,
link=Link.INPUT)
if logFile:
job.addArguments("-A", logFile)
job.uses(logFile,
transfer=transferOutput,
register=True,
link=Link.OUTPUT)
job.output = logFile
yh_pegasus.setJobProperRequirement(job, job_max_memory=job_max_memory)
workflow.addJob(job)
for input in extraDependentInputLs:
job.uses(input, transfer=True, register=True, link=Link.INPUT)
for parentJob in parentJobLs:
workflow.depends(parent=parentJob, child=job)
return job
def run(self):
"""
2011-9-28
"""
if self.debug:
import pdb
pdb.set_trace()
workflow = self.initiateWorkflow()
self.registerJars()
self.registerExecutables()
self.registerCustomExecutables(workflow)
site_handler =self.site_handler
input_site_handler = self.input_site_handler
ref_seq_f = self.registerOneInputFile(workflow, self.ref_seq_fname, folderName=self.pegasusFolderName)
query_seq_f = self.registerOneInputFile(workflow, self.query_seq_fname, folderName=self.pegasusFolderName)
# Add a mkdir job
deltaOutputDir = "delta"
deltaOutputDirJob = yh_pegasus.addMkDirJob(workflow, mkdir=self.mkdirWrap, outputDir=deltaOutputDir)
coordsOutputDir = "coords"
coordsOutputDirJob = yh_pegasus.addMkDirJob(workflow, mkdir=self.mkdirWrap, outputDir=coordsOutputDir)
filterOutputDir = "filter"
filterOutputDirJob = yh_pegasus.addMkDirJob(workflow, mkdir=self.mkdirWrap, outputDir=filterOutputDir)
plotOutputDir = "plot"
plotOutputDirJob = yh_pegasus.addMkDirJob(workflow, mkdir=self.mkdirWrap, outputDir=plotOutputDir)
#plotScriptOutputDir = "plotScript"
#plotScriptOutputDirJob = yh_pegasus.addMkDirJob(workflow, mkdir=self.mkdirWrap, outputDir=plotScriptOutputDir)
refNameLs = self.getFastaRecordTitleLs(self.ref_seq_fname)
returnData3 = self.addSplitFastaFileJobs(workflow, ref_seq_f, self.SelectAndSplitFastaRecords, refNameLs, mkdirWrap=self.mkdirWrap,\
site_handler=site_handler, namespace=self.namespace, version=self.version, fastaOutputDir='refFasta')
refName2splitFastaJobDataLs = returnData3.refName2jobDataLs
queryNameLs = self.getFastaRecordTitleLs(self.query_seq_fname)
returnData3 = self.addSplitFastaFileJobs(workflow, query_seq_f, self.SelectAndSplitFastaRecords, queryNameLs, mkdirWrap=self.mkdirWrap,\
site_handler=site_handler, namespace=self.namespace, version=self.version, fastaOutputDir='queryFasta')
queryName2splitFastaJobDataLs = returnData3.refName2jobDataLs
noOfJobs = len(refName2splitFastaJobDataLs) + len(queryName2splitFastaJobDataLs)
ref_seq_prefix = os.path.splitext(os.path.basename(ref_seq_f.name))[0]
for queryName, jobDataLs in queryName2splitFastaJobDataLs.iteritems():
for refName, refJobDataLs in refName2splitFastaJobDataLs.iteritems():
refSelectAndSplitFastaJob, refFastaFile = refJobDataLs[:2]
selectAndSplitFastaJob, fastaFile = jobDataLs[:2]
nucmerJob = Job(namespace=self.namespace, name=self.nucmer.name, version=self.version)
outputPrefix = "%s_vs_%s_%s"%(queryName, ref_seq_prefix, refName)
deltaFnamePrefix = os.path.join(deltaOutputDir, outputPrefix)
nucmerJob.addArguments("--maxgap=500", "--mincluster=100", "--prefix", deltaFnamePrefix, \
refFastaFile, fastaFile)
nucmerJob.uses(refFastaFile, transfer=False, register=True, link=Link.INPUT)
nucmerJob.uses(fastaFile, transfer=False, register=True, link=Link.INPUT)
deltaFname = "%s.delta"%(deltaFnamePrefix)
deltaF = File(deltaFname)
nucmerJob.uses(deltaFname, transfer=True, register=True, link=Link.OUTPUT)
#3000M for one nucmer job with human as ref
job_max_memory = 5000 #in MB
yh_pegasus.setJobProperRequirement(nucmerJob, job_max_memory=job_max_memory)
workflow.addJob(nucmerJob)
workflow.depends(parent=refSelectAndSplitFastaJob, child=nucmerJob)
workflow.depends(parent=selectAndSplitFastaJob, child=nucmerJob)
workflow.depends(parent=deltaOutputDirJob, child=nucmerJob)
coordsFname = os.path.join(coordsOutputDir, "%s.coords"%(outputPrefix))
coordsF = File(coordsFname)
filterFname = os.path.join(filterOutputDir, "%s.filter"%(outputPrefix))
filterF = File(filterFname)
plotPrefix = os.path.join(plotOutputDir, "%s_plot"%(outputPrefix))
png_plotF = File("%s.png"%plotPrefix)
gp_plotF = File("%s.gp"%plotPrefix)
fplot_plotF = File("%s.fplot"%plotPrefix)
rplot_plotF = File("%s.rplot"%plotPrefix)
postNucJob = Job(namespace=self.namespace, name=self.PostNucmer.name, version=self.version)
postNucJob.addArguments(deltaF, coordsF, filterF, refFastaFile, fastaFile, plotPrefix)
postNucJob.uses(deltaF, transfer=True, register=True, link=Link.INPUT)
postNucJob.uses(refFastaFile, transfer=False, register=True, link=Link.INPUT)
postNucJob.uses(fastaFile, transfer=False, register=True, link=Link.INPUT)
postNucJob.uses(coordsF, transfer=True, register=True, link=Link.OUTPUT)
postNucJob.uses(filterF, transfer=True, register=True, link=Link.OUTPUT)
postNucJob.uses(png_plotF, transfer=True, register=True, link=Link.OUTPUT)
#leave files below behind
#postNucJob.uses(gp_plotF, transfer=True, register=True, link=Link.OUTPUT)
#postNucJob.uses(fplot_plotF, transfer=True, register=True, link=Link.OUTPUT)
#postNucJob.uses(rplot_plotF, transfer=True, register=True, link=Link.OUTPUT)
yh_pegasus.setJobProperRequirement(postNucJob, job_max_memory=2000)
workflow.addJob(postNucJob)
workflow.depends(parent=nucmerJob, child=postNucJob)
workflow.depends(parent=coordsOutputDirJob, child=postNucJob)
workflow.depends(parent=filterOutputDirJob, child=postNucJob)
workflow.depends(parent=plotOutputDirJob, child=postNucJob)
#workflow.depends(parent=plotScriptOutputDirJob, child=postNucJob)
noOfJobs += 2
sys.stderr.write(" %s jobs. \n"%(noOfJobs))
# Write the DAX to stdout
outf = open(self.outputFname, 'w')
workflow.writeXML(outf)
