def Pipeline_Somatic():
testing = wga_settings['test']
target = wga_settings['target']
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval',range(1,23) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
align_to_reference = sequence_(
apply_(
reduce_(['sample_name', 'library', 'platform', 'platform_unit','sample_type','chunk','rgid'], pipes.AlignAndCleanMEM)
),
)
if target:
remove_dup = sequence_(
reduce_(['sample_name','sample_type','rgid'], picard.MERGE_SAMS)
)
else:
remove_dup = sequence_(
reduce_(['sample_name','sample_type','rgid'], picard.MarkDuplicates)
)
preprocess_alignment = sequence_(
map_(samtools.IndexBam),
apply_(
split_([intervals],gatk.RealignerTargetCreator) #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
),
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
apply_(
reduce_(['sample_name','sample_type','rgid'], gatk.BQSRGatherer),
map_(gatk.ApplyBQSR) #TODO I add BQSRGatherer as a parent with a hack inside ApplyBQSR.cmd
)
)
somatic_call = sequence_(
apply_(
sequence_(
map_(mutect.createInput),
reduce_(['rgid','interval'], mutect.Somatic, tag={'vcf': 'Mutect'}),
reduce_(['vcf'], gatk.CombineVariants, 'Combine Into Raw VCFs'),
),
sequence_(
map_(svdetect.PreProcessing),
map_(svdetect.link2SV)
)
)
)
return sequence_(
align_to_reference,
remove_dup,
preprocess_alignment,
somatic_call
)
def Pipeline_Somatic():
testing = wga_settings['test']
target = wga_settings['target']
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval', list(range(1, 23)) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
align_to_reference = sequence_(
apply_(
reduce_([
'sample_name', 'library', 'platform', 'platform_unit',
'sample_type', 'chunk', 'rgid'
], pipes.AlignAndCleanMEM)), )
if target:
remove_dup = sequence_(
reduce_(['sample_name', 'sample_type', 'rgid'], picard.MERGE_SAMS))
else:
remove_dup = sequence_(
reduce_(['sample_name', 'sample_type', 'rgid'],
picard.MarkDuplicates))
preprocess_alignment = sequence_(
map_(samtools.IndexBam),
apply_(
split_(
[intervals], gatk.RealignerTargetCreator
) #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
),
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
apply_(
reduce_(['sample_name', 'sample_type', 'rgid'], gatk.BQSRGatherer),
map_(
gatk.ApplyBQSR
) #TODO I add BQSRGatherer as a parent with a hack inside ApplyBQSR.cmd
))
somatic_call = sequence_(
apply_(
sequence_(
map_(mutect.createInput),
reduce_(['rgid', 'interval'],
mutect.Somatic,
tag={'vcf': 'Mutect'}),
reduce_(['vcf'], gatk.CombineVariants,
'Combine Into Raw VCFs'),
), sequence_(map_(svdetect.PreProcessing),
map_(svdetect.link2SV))))
return sequence_(align_to_reference, remove_dup, preprocess_alignment,
somatic_call)
def Pipeline():
testing = wga_settings['test']
target = wga_settings['target']
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval',range(1,23) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
align_to_reference = sequence_(
apply_(
reduce_(['sample_name', 'library', 'platform', 'platform_unit', 'chunk'], pipes.AlignAndCleanALN)
),
)
if target:
remove_dup = sequence_(
reduce_(['sample_name'], picard.MERGE_SAMS)
)
else:
remove_dup = sequence_(
reduce_(['sample_name'], picard.MarkDuplicates)
)
preprocess_alignment = sequence_(
map_(samtools.IndexBam),
apply_(
split_([intervals],gatk.RealignerTargetCreator) #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
),
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
apply_(
reduce_(['sample_name'], gatk.BQSRGatherer),
map_(gatk.ApplyBQSR) #TODO I add BQSRGatherer as a parent with a hack inside ApplyBQSR.cmd
)
)
call_variants = sequence_(
apply_(
#reduce_(['interval'],gatk.HaplotypeCaller,tag={'vcf':'HaplotypeCaller'}),
reduce_split_(['interval'], [glm], gatk.UnifiedGenotyper, tag={'vcf': 'UnifiedGenotyper'}),
combine=True
),
reduce_(['vcf'], gatk.CombineVariants, 'Combine Into Raw VCFs'),
split_([glm],gatk.VQSR),
)
return sequence_(
align_to_reference,
remove_dup,
preprocess_alignment,
call_variants
)
def Pipeline():
testing = wga_settings['test']
target = wga_settings['target']
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval', list(range(1, 23)) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
align_to_reference = sequence_(
apply_(
reduce_([
'sample_name', 'library', 'platform', 'platform_unit', 'chunk'
], pipes.AlignAndCleanALN)), )
if target:
remove_dup = sequence_(reduce_(['sample_name'], picard.MERGE_SAMS))
else:
remove_dup = sequence_(reduce_(['sample_name'], picard.MarkDuplicates))
preprocess_alignment = sequence_(
map_(samtools.IndexBam),
apply_(
split_(
[intervals], gatk.RealignerTargetCreator
) #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
),
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
apply_(
reduce_(['sample_name'], gatk.BQSRGatherer),
map_(
gatk.ApplyBQSR
) #TODO I add BQSRGatherer as a parent with a hack inside ApplyBQSR.cmd
))
call_variants = sequence_(
apply_(
#reduce_(['interval'],gatk.HaplotypeCaller,tag={'vcf':'HaplotypeCaller'}),
reduce_split_(['interval'], [glm],
gatk.UnifiedGenotyper,
tag={'vcf': 'UnifiedGenotyper'}),
combine=True),
reduce_(['vcf'], gatk.CombineVariants, 'Combine Into Raw VCFs'),
split_([glm], gatk.VQSR),
)
return sequence_(align_to_reference, remove_dup, preprocess_alignment,
call_variants)
def Pipeline_split():
split_fastq = sequence_(
map_(json_.Split), apply_(reduce_(['gz_output_dir'],
json_.Total_json)),
map_(json_.Format_json))
return sequence_(split_fastq, )
def Pipeline_local():
testing = wga_settings['test']
target = wga_settings['target']
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval',range(1,23) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
print [glm][0]
align_to_reference = sequence_(
apply_(
reduce_(['sample_name', 'library', 'platform', 'platform_unit'], pipes.AlignAndCleanALN)
),
)
if target:
remove_dup = sequence_(
)
else:
remove_dup = sequence_(
reduce_(['sample_name'], picard.MarkDuplicates)
)
preprocess_alignment = sequence_(
map_(samtools.IndexBam),
map_(gatk.RealignerTargetCreator), #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
map_(gatk.ApplyBQSR_local)
)
call_variants = sequence_(
apply_(
map_(gatk.UnifiedGenotyper_local, tag={'vcf': 'UnifiedGenotyper'})
)
)
return sequence_(
align_to_reference,
remove_dup,
preprocess_alignment,
call_variants
)
def Pipeline_split():
split_fastq = sequence_(
map_(json_.Split),
apply_(
reduce_(['gz_output_dir'],json_.Total_json)
),
map_(json_.Format_json)
)
return sequence_(
split_fastq,
)
def Pipeline_local():
testing = wga_settings['test']
target = wga_settings['target']
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval', list(range(1, 23)) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
print([glm][0])
align_to_reference = sequence_(
apply_(
reduce_(['sample_name', 'library', 'platform', 'platform_unit'],
pipes.AlignAndCleanALN)), )
if target:
remove_dup = sequence_()
else:
remove_dup = sequence_(reduce_(['sample_name'], picard.MarkDuplicates))
preprocess_alignment = sequence_(
map_(samtools.IndexBam),
map_(
gatk.RealignerTargetCreator
), #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
map_(gatk.ApplyBQSR_local))
call_variants = sequence_(
apply_(
map_(gatk.UnifiedGenotyper_local, tag={'vcf':
'UnifiedGenotyper'})))
return sequence_(align_to_reference, remove_dup, preprocess_alignment,
call_variants)
def Pipeline():
is_capture = wga_settings['capture']
testing = wga_settings['test']
# split_ tuples
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval', range(1, 23) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
align_to_reference = sequence_(
apply_(
reduce_(['sample_name', 'library'], misc.FastqStats),
reduce_([
'sample_name', 'library', 'platform', 'platform_unit', 'chunk'
], pipes.AlignAndClean)), )
preprocess_alignment = sequence_(
reduce_(['sample_name'], picard.MarkDuplicates),
apply_(
map_(picard.CollectMultipleMetrics),
split_(
[intervals], gatk.RealignerTargetCreator
) #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
),
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
apply_(
reduce_(['sample_name'], gatk.BQSRGatherer),
map_(
gatk.ApplyBQSR
) #TODO I add BQSRGatherer as a parent with a hack inside ApplyBQSR.cmd
))
call_variants = sequence_(
# apply_(
# reduce_split_([],[intervals,glm], gatk.UnifiedGenotyper, tag={'vcf': 'UnifiedGenotyper'}),
# combine=True
# ) if is_capture
# else
apply_(
#reduce_(['interval'],gatk.HaplotypeCaller,tag={'vcf':'HaplotypeCaller'}),
reduce_split_(['interval'], [glm],
gatk.UnifiedGenotyper,
tag={'vcf': 'UnifiedGenotyper'}),
combine=True),
reduce_(['vcf'], gatk.CombineVariants, 'Combine Into Raw VCFs'),
split_([glm], gatk.VQSR),
map_(gatk.Apply_VQSR),
reduce_(['vcf'], gatk.CombineVariants, "Combine into Master VCFs"))
if is_capture:
return sequence_(align_to_reference, preprocess_alignment,
call_variants, massive_annotation)
else:
return sequence_(
align_to_reference, preprocess_alignment,
reduce_split_(['sample_name'], [intervals], gatk.ReduceReads),
call_variants, massive_annotation)
def Pipeline():
is_capture = wga_settings['capture']
testing = wga_settings['test']
# split_ tuples
if testing:
intervals = ('interval', [20])
else:
intervals = ('interval',range(1,23) + ['X', 'Y'])
glm = ('glm', ['SNP', 'INDEL'])
align_to_reference = sequence_(
apply_(
reduce_(['sample_name', 'library'], misc.FastqStats),
reduce_(['sample_name', 'library', 'platform', 'platform_unit', 'chunk'], pipes.AlignAndClean)
),
)
preprocess_alignment = sequence_(
reduce_(['sample_name'], picard.MarkDuplicates),
apply_(
map_(picard.CollectMultipleMetrics),
split_([intervals],gatk.RealignerTargetCreator) #if not is_capture or testing else map_(gatk.RealignerTargetCreator)
),
map_(gatk.IndelRealigner),
map_(gatk.BQSR),
apply_(
reduce_(['sample_name'], gatk.BQSRGatherer),
map_(gatk.ApplyBQSR) #TODO I add BQSRGatherer as a parent with a hack inside ApplyBQSR.cmd
)
)
call_variants = sequence_(
# apply_(
# reduce_split_([],[intervals,glm], gatk.UnifiedGenotyper, tag={'vcf': 'UnifiedGenotyper'}),
# combine=True
# ) if is_capture
# else
apply_(
#reduce_(['interval'],gatk.HaplotypeCaller,tag={'vcf':'HaplotypeCaller'}),
reduce_split_(['interval'], [glm], gatk.UnifiedGenotyper, tag={'vcf': 'UnifiedGenotyper'}),
combine=True
),
reduce_(['vcf'], gatk.CombineVariants, 'Combine Into Raw VCFs'),
split_([glm],gatk.VQSR),
map_(gatk.Apply_VQSR),
reduce_(['vcf'], gatk.CombineVariants, "Combine into Master VCFs")
)
if is_capture:
return sequence_(
align_to_reference,
preprocess_alignment,
call_variants,
massive_annotation
)
else:
return sequence_(
align_to_reference,
preprocess_alignment,
reduce_split_(['sample_name'],[intervals],gatk.ReduceReads),
call_variants,
massive_annotation
)