def test_pipes():
ParslPipeline._pipeline_run_temp_dir = tempfile.TemporaryDirectory(
dir='/tmp', suffix='__operon')
one = Software('one', path='/path/to/one')
pipe = Pipe(
one.prep(Parameter('-a', '1'), Parameter('-b', '2'),
Redirect(stream='>', dest='/path/to/log')))
assert isinstance(pipe.piped_software_blueprint, dict)
def test_parameters():
p_single = Parameter('one')
p_multiple = Parameter('-a', 'one', '-b', 'two')
p_equals = Parameter('--one', 'a', sep='=')
p_fused = Parameter('-a one -b', 'two')
p_with_data1 = Parameter(Data('/path/to/data'))
p_with_data2 = Parameter('-a', Data('/path/to/data1'),
Data('/path/to/data2'))
# Parameters turn into strings as expected
assert str(p_single) == 'one'
assert str(p_multiple) == '-a one -b two'
assert str(p_equals) == '--one=a' # Use with different separators
assert str(
p_fused
) == '-a one -b two' # Spaces in single string handled correctly
# Holds Data objects correctly
assert len(p_single.data) == 0 and not p_single.data
assert len(p_with_data1.data) == 1
assert len(p_with_data2.data) == 2
assert str(p_with_data1.data[0]) == '/path/to/data'
assert str(p_with_data2) == '-a /path/to/data1 /path/to/data2'
def pipeline(self, pipeline_args, pipeline_config):
# chunky run RiboSeq_pipe.py --fastqs
# /mnt/cinder/thomas/RiboSeq/Lane5/AWS-3_S3_L005_R1_001.fastq.gz
# --output /mnt/cinder/thomas/RiboSeq/test --threads
# create variables from parser if wanted
bamFiles = pipeline_args['bam:lib']
outputDir = pipeline_args['output']
numThreads = pipeline_args['threads']
# Create output directory
subprocess.call(['mkdir', outputDir])
# Software
bedtools = Software('bedtools', pipeline_config['bedtools']['path'])
samtools = Software('samtools', pipeline_config['samtools']['path'])
samtools_header = Software('samtools', pipeline_config['samtools']['path'])
samtools_uniq = Software('samtools', pipeline_config['samtools']['path'])
samtools_sort = Software('samtools sort', pipeline_config['samtools']['path'])
read_distribution = Software('read_distribution',
pipeline_config['read_distribution']['path'])
featureCounts = Software('featureCounts', pipeline_config['featureCounts']['path'])
fastQC = Software('FastQC', pipeline_config['FastQC']['path'])
picard = Software('picard', "java -Xms8g -Xmx9g -jar {}".format(pipeline_config['picard']['path']))
# Change these to just be done in python script?
# Common software tools
awk = Software('awk', 'awk')
sort = Software('sort', 'sort')
uniq = Software('uniq', 'uniq')
paste = Software('paste', 'paste')
cat = Software('cat', 'cat')
grep = Software('grep', 'grep')
# Directories and Files
pathToGtf = pipeline_config['star']['GTF_ref']
pathTo_hg19_bed = pipeline_config['read_distribution']['hg19_bed']
pathTo_hg19_bed_start100 = pipeline_config['bedtools']['hg19_start100']
pathTo_grch37_bed = pipeline_config['bedtools']['grch37_bed']
pathTo_genomeFasta = pipeline_config['picard']['genomeFasta']
pathTo_ref_flat = pipeline_config['picard']['refFlat']
# bid_list = []
# for fastqlib in fastqFiles:
# bid_list.append(fastqlib.split(':')[-1])
for bamlib in bamFiles:
bam, bid = bamlib.split(':')
newDir = os.path.join(outputDir, bid)
subprocess.call(['mkdir', newDir])
uniq_bam = '{}/{}.uniq_sorted.bam'.format(newDir, bid)
samtools_uniq.register(
Parameter('view'),
Parameter(Data(bam).as_input()), # star outfile name
Pipe(
grep.prep(
Parameter('-w'),
Parameter('NH:i:1'),
Pipe(
cat.prep(
Parameter(os.path.join(newDir, '{}.header.sam'.format(bid)), '-'),
Pipe(
samtools.prep(
Parameter('view'),
Parameter('-bS', '-'),
Pipe(
samtools.prep(
Parameter('sort'),
Parameter('-', '-o', Data(uniq_bam).as_output())
)
)
)
)
)
)
)
)
)
# QC
# Codon_periodicity
intersectBed_filepath = '{}/{}.intersect_start100.bed'.format(newDir, bid)
relative_pos_table_filepath = '{}/{}_relative_pos_aggregate.table'.format(newDir, bid)
bedtools.register(
Parameter('intersect'),
Parameter('-a {}'.format(pathTo_hg19_bed_start100)),
Parameter('-b', Data(uniq_bam).as_input()),
Parameter('-s'),
Parameter('-bed'),
Parameter('-wa'),
Parameter('-wb'),
Redirect(stream=Redirect.STDOUT, dest=os.path.join(newDir,
'{}.intersect_start100.bed'.format(bid))),
extra_outputs=[Data(intersectBed_filepath).as_output()]
)
CodeBlock.register(
func=relative_pos_table,
args=[],
kwargs={'intersect_bedtools_filepath' : intersectBed_filepath,
'relativePos_filepath': relative_pos_table_filepath},
inputs=[Data(intersectBed_filepath).as_input()],
outputs=[Data(relative_pos_table_filepath).as_output()]
)
codon_periodicity_filepath = '{}/{}_codon_periodicity_plot.png'.format(newDir, bid)
CodeBlock.register(
func=create_codon_periodicity,
args=[],
kwargs={'relativePos_filepath': relative_pos_table_filepath,
'codon_periodicity_filepath' : codon_periodicity_filepath},
inputs=[Data(relative_pos_table_filepath).as_input()],
outputs=[Data(codon_periodicity_filepath).as_output()]
)
# Picard
picard.register(
Parameter('CollectMultipleMetrics'),
Parameter('I={}'.format(uniq_bam)), # input
Parameter('O={}/{}.multiple_metrics'.format(newDir, bid)), # output
Parameter('R={}'.format(pathTo_genomeFasta)), # genomeReference
extra_inputs=[Data(uniq_bam)]
)
picard.register(
Parameter('CollectGcBiasMetrics'),
Parameter('I={}'.format(uniq_bam)),
Parameter('O={}/{}.gc_bias_metrics'.format(newDir, bid)), # output
Parameter('CHART={}/{}.gc_bias_metrics.pdf'.format(newDir, bid)), # chart
Parameter('S={}/{}.summary_metrics'.format(newDir, bid)), # summary metrics
Parameter('R={}'.format(pathTo_genomeFasta)), # genome reference
extra_inputs=[Data(uniq_bam)]
)
picard.register(
Parameter('CollectRnaSeqMetrics'),
Parameter('I={}'.format(uniq_bam)),
Parameter('O={}/{}.RNA_Metrics'.format(newDir, bid)), # output
Parameter('REF_FLAT={}'.format('{}'.format(pathTo_ref_flat))), # ref_flat
Parameter('STRAND=FIRST_READ_TRANSCRIPTION_STRAND'), # strandedness
extra_inputs=[Data(uniq_bam)]
)
picard.register(
Parameter('MarkDuplicates'),
Parameter('I={}'.format(uniq_bam)),
Parameter('O={}/{}.marked_duplicates.bam'.format(newDir, bid)), # output
Parameter('M={}/{}.marked_dup_metrics.txt'.format(newDir, bid)), # marked dup metrics
Parameter('ASSUME_SORTED=true'), # It is sorted
extra_inputs=[Data(uniq_bam)]
)
# featureCounts
featureCounts.register(
Parameter('-a', Data('{}'.format(pathToGtf)).as_input()), # gtf
Parameter('-s', '1'), # strand-specific read counting
Parameter('-o', '{}/{}.featureCounts'.format(newDir, bid)), # output
Parameter(Data(uniq_bam).as_input()) # input
)
# fastQC
# fastQC.register(
# Parameter('--outdir={}'.format(newDir)), # output
# Parameter('--t', numThreads),
# Parameter(Data(fastq).as_input())
# )
# read_distribution
read_distribution.register(
Parameter('-r'),
Parameter(Data(pathTo_hg19_bed).as_input()),
Parameter('-i'),
Parameter(Data(uniq_bam).as_input()),
Redirect(stream=Redirect.STDOUT, dest=os.path.join(newDir,
'{}.read_distribution.log'.format(bid)))
)
def pipeline(self, pipeline_args, pipeline_config):
tmpdir = tempfile.mkdtemp()
os.chdir(tmpdir)
wget = Software('wget')
ersatz = Software('ersatz')
star = Software('STAR', subprogram='twopass')
wget.register(
Parameter(
'https://lh3.googleusercontent.com/'
'8gaEOU2p30N4Up-KMUl4MQBtnn0F5DyH5bqKKr0QqptnQgPk4lxXaWLJhi8Dcu9i8qE=w170'
),
Parameter('-O',
Data(os.path.join(tmpdir, 'image.png')).as_output()))
master = ersatz.register()
ersatz.register(wait_on=[master])
ersatz.register(wait_on=[master])
ersatz.register(wait_on=[master])
ersatz.register(wait_on=[master])
# Ersatz2 (2)
ersatz.register(
Parameter('--inputs',
Data(os.path.join(tmpdir, 'image.png')).as_input()),
Parameter('--outputs',
Data('21.out').as_output(),
Data('22.out').as_output()))
# Ersatz1 (3)
ersatz.register(Parameter('--outputs', Data('11.out').as_output()))
# Ersatz3 (4)
ersatz.register(Parameter('--outputs', Data('31.out').as_output()))
# Ersatz4 (5)
ersatz4 = ersatz.register(
Parameter('--inputs',
Data('11.out').as_input(),
Data('21.out').as_input()),
Parameter('--outputs',
Data('41.out').as_output(),
Data('42.out').as_output()))
# Ersatz5 (6)
ersatz.register(
Parameter('--inputs',
Data('22.out').as_input(),
Data('31.out').as_input()),
Parameter('--outputs',
Data('51.out').as_output()),
wait_on=[ersatz4] # TODO Software as dependencies
)
# Ersatz6 (7)
ersatz.register(
Parameter('--inputs',
Data('41.out').as_input(),
Data('42.out').as_input(),
Data('51.out').as_input()),
Parameter('--outputs',
Data('61.out').as_output()))
def test_software():
# Reset app_id counter
_ParslAppBlueprint._id_counter = 0
# Set temp dir
ParslPipeline._pipeline_run_temp_dir = tempfile.TemporaryDirectory(
dir='/tmp', suffix='__operon')
# Spoof pipeline config
Software._pipeline_config = {
'software1': {
'path': '/path/to/soft1'
},
'software2': {
'path': '/path/to/soft2',
'one': 'two'
},
'bwa_mem': {
'path': '/path/to/bwa mem'
}
}
# Create Software instances
software1 = Software('software1')
software2 = Software('software2', subprogram='sub')
assert software2.basename == 'soft2'
software3 = Software('software3', path='/path/to/soft3')
software4 = Software('software4', path='/path/to/soft4', subprogram='four')
assert software4.path == '/path/to/soft4 four'
bwa_mem = Software('bwa_mem')
assert bwa_mem.path == '/path/to/bwa mem'
assert bwa_mem.basename == 'bwa_mem'
# Raise ValueError when software path cannot be inferred
with pytest.raises(ValueError):
software5 = Software('software5')
# With different success codes
software6 = Software('software6',
path='/path/to/soft6',
success_on=['0', '1', '128'])
# Registering properly adds to blueprints
software1.register(Parameter('-a', 'one'),
Redirect(stream='>', dest='/path/to/dest'))
assert len(_ParslAppBlueprint._blueprints) == 1
assert list(_ParslAppBlueprint._blueprints.keys()) == ['soft1_1']
# .prep() unique ID per call
assert software2.prep()['id'] != software2.prep()['id']
# inputs, outputs, wait_on, stdout, stderr lists properly populated
# Proper handling of Data objects
_def_soft3 = software3.register(Parameter('-a', 'one'))
assert isinstance(_def_soft3, _DeferredApp)
_soft4_blueprint = software4.prep(
Parameter('-a',
Data('/input1.txt').as_input()),
Parameter('-b',
Data('/input2.txt').as_input()),
Parameter('--outfile',
Data('/output1.txt').as_output()),
Redirect(stream='>', dest='/stdout.log'),
Redirect(stream=Redirect.STDERR, dest=Data('/stderr.log')),
extra_inputs=[Data('/input3.txt'),
Data('/input4.txt')],
extra_outputs=[Data('/output2.txt'),
Data('/output3.txt')],
wait_on=[_def_soft3])
assert sorted(_soft4_blueprint['inputs']) == [
'/input{}.txt'.format(i) for i in range(1, 5)
]
assert sorted(_soft4_blueprint['outputs']
) == ['/output{}.txt'.format(i)
for i in range(1, 4)] + ['/stderr.log']
assert len(_soft4_blueprint['wait_on']) == 1
assert _soft4_blueprint['wait_on'][0] == _def_soft3.app_id
assert _soft4_blueprint['stdout'] == '/stdout.log'
assert _soft4_blueprint['stderr'] == '/stderr.log'
# Proper handling of Pipe
_piped_soft1_soft6 = software1.prep(
Parameter('-a', '1'),
Redirect(stream='>',
dest='/ignored.out'), # This should be overridden by Pipe
Pipe(
software6.prep(Parameter('-b', '2'),
Parameter('-c',
Data('/piped.out').as_input()),
Redirect(stream='>', dest='/piped.log'))))
assert _piped_soft1_soft6['cmd'].count('|') == 1
assert _piped_soft1_soft6['stdout'] == '/piped.log'
assert len(_piped_soft1_soft6['inputs']) == 1
assert _piped_soft1_soft6['inputs'][0] == '/piped.out'
# Ignore extra Redirects
_ignore_redir = software2.prep(
Parameter('-a', '1'), Redirect(stream='>', dest='/real.out'),
Redirect(stream='2>', dest='/real.err'),
Redirect(stream='>', dest='/ignored.out'),
Redirect(stream='>', dest='/also_ignored.out'),
Redirect(stream='2>', dest='/also_ignored.err'))
assert _ignore_redir['stdout'] == '/real.out'
assert _ignore_redir['stderr'] == '/real.err'
# Ignore extra pipes
_ignore_pipe = software2.prep(
Parameter('-d', 'honeysucklerose'),
Pipe(software1.prep(Parameter('-a', 'real'))),
Pipe(software4.prep(Parameter('-b', 'ignored'))))
assert _ignore_pipe['cmd'].count('|') == 1
assert 'ignored' not in _ignore_pipe['cmd']
assert 'real' in _ignore_pipe['cmd']
# Sending stdout/stderr to temporary file
_stdout_stderr_tmp = software6.prep(Parameter('-a', 'ella'))
assert _stdout_stderr_tmp['stdout'] is not None
assert _stdout_stderr_tmp['stdout'].endswith('.stdout')
assert _stdout_stderr_tmp['stderr'] is not None
assert _stdout_stderr_tmp['stderr'].endswith('.stderr')
def pipeline_components_for_tests():
# Instantiate software
petrichor = Software(
'petrichor',
'/home/dfitzgerald/workspace/PycharmProjects/Operon/tests/petrichor')
bash_sleep = Software('bash_sleep', '/bin/sleep')
# Define python app
def notos(sleep=None, outs=None):
import time
import random
id_ = random.randint(1, 1000)
if sleep:
time.sleep(sleep)
if outs:
for out in outs:
with open(out, 'w') as outfile:
outfile.write('{}\n'.format(id_))
# App a, start=0, end=2
petrichor.register(Parameter('--sleep', '2'),
Redirect(stream='>', dest=Data('a.out')))
# App b, start=0, end=3
petrichor.register(Parameter('--sleep', '3'),
Redirect(stream='>', dest=Data('b.out')))
# App c, start=0, end=5
petrichor.register(Parameter('--sleep', '5'),
Redirect(stream='>', dest=Data('c.out')))
# App d, start=5, end=8
CodeBlock.register(func=notos,
kwargs={
'sleep': 3,
'outs': ['d1.out', 'd2.out']
},
inputs=[Data('a.out'),
Data('b.out'),
Data('c.out')],
outputs=[Data('d1.out'), Data('d2.out')])
# App e, start=0, end=10
app_e = bash_sleep.register(Parameter('10'))
# App g, start=10, end=12
CodeBlock.register(func=notos,
kwargs={
'sleep': 2,
'outs': ['g1.out', 'g2.out']
},
inputs=[Data('d2.out')],
outputs=[Data('g1.out'), Data('g2.out')],
wait_on=[app_e])
# App f, start=8, end=11
petrichor.register(Parameter('--sleep', '3'),
Parameter('--outfile',
Data('f.out').as_output(tmp=True)),
extra_inputs=[Data('d1.out')])
# App h, start=12, end=18
app_h = bash_sleep.register(Parameter('6'), extra_inputs=[Data('g2.out')])
# App i, start=18, end=20
petrichor.register(Parameter('--sleep', '2'),
Parameter('--outfile',
Data('i.final').as_output()),
extra_inputs=[Data('g1.out'),
Data('f.out')],
wait_on=[app_h])
def multipipeline_components_for_tests():
# Instantiate software
petrichor = Software(
'petrichor',
'/home/dfitzgerald/workspace/PycharmProjects/Operon/tests/petrichor')
bash_sleep = Software('bash_sleep', '/bin/sleep')
# Define python app
def notos(sleep=None, outs=None):
import time
import random
id_ = random.randint(1, 1000)
if sleep:
time.sleep(sleep)
if outs:
for out in outs:
with open(out, 'w') as outfile:
outfile.write('{}\n'.format(id_))
Meta.define_executor(label='small', resources={'cpu': '1', 'mem': '1G'})
Meta.define_executor(label='med', resources={'cpu': '2', 'mem': '2G'})
Meta.define_executor(label='large', resources={'cpu': '3', 'mem': '3G'})
# App a, start=0, end=2
# petrichor_1
petrichor.register(Parameter('--sleep', '2'),
Redirect(stream='>', dest=Data('a.out')),
meta={'executor': 'small'})
# App b, start=0, end=3
# petrichor_2
petrichor.register(Parameter('--sleep', '3'),
Redirect(stream='>', dest=Data('b.out')),
meta={'executor': 'med'})
# App c, start=0, end=5
# petrichor_3
petrichor.register(Parameter('--sleep', '5'),
Redirect(stream='>', dest=Data('c.out')),
meta={'executor': 'large'})
# App d, start=5, end=8
# notos_4
CodeBlock.register(func=notos,
kwargs={
'sleep': 3,
'outs': ['d1.out', 'd2.out']
},
inputs=[Data('a.out'),
Data('b.out'),
Data('c.out')],
outputs=[Data('d1.out'), Data('d2.out')],
meta={'executor': 'small'})
# App e, start=0, end=10
# sleep_5
app_e = bash_sleep.register(Parameter('10'), meta={'executor': 'med'})
# App g, start=10, end=12
# notos_6
CodeBlock.register(func=notos,
kwargs={
'sleep': 2,
'outs': ['g1.out', 'g2.out']
},
inputs=[Data('d2.out')],
outputs=[Data('g1.out'), Data('g2.out')],
wait_on=[app_e],
meta={'executor': 'small'})
# App f, start=8, end=11
# petrichor_7
petrichor.register(Parameter('--sleep', '3'),
Parameter('--outfile',
Data('f.out').as_output(tmp=True)),
extra_inputs=[Data('d1.out')],
meta={'executor': 'med'})
# App h, start=12, end=18
# sleep_8
app_h = bash_sleep.register(Parameter('6'),
extra_inputs=[Data('g2.out')],
meta={'executor': 'large'})
# App i, start=18, end=20
# petrichor_9
petrichor.register(Parameter('--sleep', '2'),
Parameter('--outfile',
Data('i.final').as_output()),
extra_inputs=[Data('g1.out'),
Data('f.out')],
wait_on=[app_h],
meta={'executor': 'small'})
def pipeline(self, pipeline_args, pipeline_config):
# chunky run RiboSeq_pipe.py --fastqs
# /mnt/cinder/thomas/RiboSeq/Lane5/AWS-3_S3_L005_R1_001.fastq.gz
# --output /mnt/cinder/thomas/RiboSeq/test --threads
# create variables from parser if wanted
fastqFiles = pipeline_args['fastq:lib']
outputDir = pipeline_args['output']
adapter = pipeline_args['adapter']
numThreads = pipeline_args['threads']
# Create output directory
subprocess.call(['mkdir', outputDir])
# Software
cutadapt = Software('cutadapt', pipeline_config['cutadapt']['path'])
star = Software('star', pipeline_config['star']['path'])
bedtools = Software('bedtools', pipeline_config['bedtools']['path'])
bowtie2 = Software('bowtie2', pipeline_config['bowtie2']['path'])
samtools = Software('samtools', pipeline_config['samtools']['path'])
samtools_header = Software('samtools',
pipeline_config['samtools']['path'])
samtools_uniq = Software('samtools',
pipeline_config['samtools']['path'])
samtools_sort = Software('samtools sort',
pipeline_config['samtools']['path'])
read_distribution = Software(
'read_distribution', pipeline_config['read_distribution']['path'])
featureCounts = Software('featureCounts',
pipeline_config['featureCounts']['path'])
fastQC = Software('FastQC', pipeline_config['FastQC']['path'])
picard = Software(
'picard', "java -Xms8g -Xmx9g -jar {}".format(
pipeline_config['picard']['path']))
# Change these to just be done in python script?
# Common software tools
awk = Software('awk', 'awk')
sort = Software('sort', 'sort')
uniq = Software('uniq', 'uniq')
paste = Software('paste', 'paste')
cat = Software('cat', 'cat')
grep = Software('grep', 'grep')
# Directories and Files
pathToGenomeDir = pipeline_config['star']['genomeDir']
pathToGenome = pipeline_config['bowtie2']['genome_ref']
pathToGtf = pipeline_config['star']['GTF_ref']
pathTo_hg19_bed = pipeline_config['read_distribution']['hg19_bed']
pathTo_hg19_bed_start100 = pipeline_config['bedtools']['hg19_start100']
pathTo_grch37_bed = pipeline_config['bedtools']['grch37_bed']
pathTo_genomeFasta = pipeline_config['picard']['genomeFasta']
pathTo_ref_flat = pipeline_config['picard']['refFlat']
# bid_list = []
# for fastqlib in fastqFiles:
# bid_list.append(fastqlib.split(':')[-1])
for fastqlib in fastqFiles:
fastq, bid = fastqlib.split(':')
# Make new directories to store data
newDir = os.path.join(outputDir, bid)
subprocess.call(['mkdir', newDir])
trimmed_read_filename = '{}/{}.trimmed.fastq.gz'.format(
newDir, bid)
cutadapt.register(
Parameter('--quality-base=33'),
Parameter('--minimum-length=25'),
Parameter('--discard-untrimmed'),
Parameter('--output={}'.format(trimmed_read_filename)),
# Parameter('--cores', numThreads),
Parameter('-a', adapter),
Parameter(Data(fastq).as_input()),
Redirect(stream=Redirect.STDOUT,
dest=os.path.join(
newDir, '{}.cutadapt.summary.log'.format(bid))),
extra_outputs=[
Data(trimmed_read_filename).as_output(tmp=True)
])
bowtie2.register(
Parameter('--seedlen=23'),
Parameter('--threads', numThreads),
Parameter(
'--un-gz',
Data('{}/{}.filtered.fastq.gz'.format(newDir,
bid)).as_output()),
Parameter(
'-x',
Data(
pathToGenome).as_input()), # Path to rtsRNA_seqs files
Parameter('-U',
Data(trimmed_read_filename).as_input()),
Parameter('-S'),
Parameter(
Data('{}/{}.rts.sam'.format(newDir,
bid)).as_output(tmp=True)),
Redirect(stream=Redirect.STDOUT,
dest=os.path.join(newDir,
'{}.bowtie2.log'.format(bid))),
Redirect(stream=Redirect.STDERR,
dest=os.path.join(newDir,
'{}.bowtie2.log2'.format(bid))))
samtools.register(
Parameter('view'),
Parameter('-Sb'),
Parameter(
Data('{}/{}.rts.sam'.format(newDir, bid)).as_input()),
Redirect(stream=Redirect.STDOUT,
dest=os.path.join(newDir, '{}.rts.bam'.format(bid))),
)
star.register(
Parameter(
'--runThreadN',
numThreads), # Change to command line parameter --threads
Parameter('--sjdbGTFfile', pathToGtf),
Parameter('--outSAMtype', 'BAM', 'Unsorted'),
Parameter('--outFileNamePrefix', '{}/{}_'.format(newDir, bid)),
Parameter('--genomeDir', pathToGenomeDir),
# Parameter('--genomeLoad', genomeLoad), broken
Parameter(
'--readFilesIn',
Data('{}/{}.filtered.fastq.gz'.format(newDir,
bid)).as_input()),
Parameter('--readFilesCommand zcat'), # reads gzipped files
extra_outputs=[
Data('{}/{}.Aligned.bam'.format(newDir, bid)).as_output()
])
samtools_header.register(
Parameter('view'),
Parameter('-H'),
Parameter(
Data('{}/{}.Aligned.bam'.format(
newDir, bid)).as_input()), # star outfile name
Redirect(stream=Redirect.STDOUT,
dest=os.path.join(newDir,
'{}.header.sam'.format(bid))),
extra_outputs=[
Data('{}/{}.header.sam'.format(newDir, bid)).as_output()
])
uniq_bam = '{}/{}.uniq_sorted.bam'.format(newDir, bid)
samtools_uniq.register(
Parameter('view'),
Parameter(
Data('{}/{}.Aligned.bam'.format(
newDir, bid)).as_input()), # star outfile name
Pipe(
grep.prep(
Parameter('-w'), Parameter('NH:i:1'),
Pipe(
cat.prep(
Parameter(
os.path.join(newDir,
'{}.header.sam'.format(bid)),
'-'),
Pipe(
samtools.prep(
Parameter('view'),
Parameter('-bS', '-'),
Pipe(
samtools.prep(
Parameter('sort'),
Parameter(
'-', '-o',
Data(uniq_bam).as_output())
)))))))))
# QC
# Codon_periodicity
intersectBed_filepath = '{}/{}.intersect_start100.bed'.format(
newDir, bid)
relative_pos_table_filepath = '{}/{}_relative_pos_aggregate.table'.format(
newDir, bid)
bedtools.register(
Parameter('intersect'),
Parameter('-a {}'.format(pathTo_hg19_bed_start100)),
Parameter('-b',
Data(uniq_bam).as_input()),
Parameter('-s'),
Parameter('-bed'),
Parameter('-wa'),
Parameter('-wb'),
Redirect(stream=Redirect.STDOUT,
dest=os.path.join(
newDir, '{}.intersect_start100.bed'.format(bid))),
extra_outputs=[Data(intersectBed_filepath).as_output()])
CodeBlock.register(
func=relative_pos_table,
args=[],
kwargs={
'intersect_bedtools_filepath': intersectBed_filepath,
'relativePos_filepath': relative_pos_table_filepath
},
inputs=[Data(intersectBed_filepath).as_input()],
outputs=[Data(relative_pos_table_filepath).as_output()])
codon_periodicity_filepath = '{}/{}_codon_periodicity_plot.png'.format(
newDir, bid)
CodeBlock.register(
func=create_codon_periodicity,
args=[],
kwargs={
'relativePos_filepath': relative_pos_table_filepath,
'codon_periodicity_filepath': codon_periodicity_filepath
},
inputs=[Data(relative_pos_table_filepath).as_input()],
outputs=[Data(codon_periodicity_filepath).as_output()])
# Picard
picard.register(
Parameter('CollectMultipleMetrics'),
Parameter('I={}'.format(uniq_bam)), # input
Parameter('O={}/{}.multiple_metrics'.format(newDir,
bid)), # output
Parameter(
'R={}'.format(pathTo_genomeFasta)), # genomeReference
extra_inputs=[Data(uniq_bam)])
picard.register(
Parameter('CollectGcBiasMetrics'),
Parameter('I={}'.format(uniq_bam)),
Parameter('O={}/{}.gc_bias_metrics'.format(newDir,
bid)), # output
Parameter('CHART={}/{}.gc_bias_metrics.pdf'.format(
newDir, bid)), # chart
Parameter('S={}/{}.summary_metrics'.format(
newDir, bid)), # summary metrics
Parameter(
'R={}'.format(pathTo_genomeFasta)), # genome reference
extra_inputs=[Data(uniq_bam)])
picard.register(
Parameter('CollectRnaSeqMetrics'),
Parameter('I={}'.format(uniq_bam)),
Parameter('O={}/{}.RNA_Metrics'.format(newDir, bid)), # output
Parameter('REF_FLAT={}'.format(
'{}'.format(pathTo_ref_flat))), # ref_flat
Parameter(
'STRAND=FIRST_READ_TRANSCRIPTION_STRAND'), # strandedness
extra_inputs=[Data(uniq_bam)])
picard.register(
Parameter('MarkDuplicates'),
Parameter('I={}'.format(uniq_bam)),
Parameter('O={}/{}.marked_duplicates.bam'.format(
newDir, bid)), # output
Parameter('M={}/{}.marked_dup_metrics.txt'.format(
newDir, bid)), # marked dup metrics
Parameter('ASSUME_SORTED=true'), # It is sorted
extra_inputs=[Data(uniq_bam)])
# featureCounts
featureCounts.register(
Parameter('-a',
Data('{}'.format(pathToGtf)).as_input()), # gtf
Parameter('-s', '1'), # strand-specific read counting
Parameter('-o', '{}/{}.featureCounts'.format(newDir,
bid)), # output
Parameter(Data(uniq_bam).as_input()) # input
)
# fastQC
fastQC.register(
Parameter('--outdir={}'.format(newDir)), # output
Parameter('--t', numThreads),
Parameter(Data(fastq).as_input()))
# read_distribution
read_distribution.register(
Parameter('-r'), Parameter(Data(pathTo_hg19_bed).as_input()),
Parameter('-i'), Parameter(Data(uniq_bam).as_input()),
Redirect(stream=Redirect.STDOUT,
dest=os.path.join(
newDir, '{}.read_distribution.log'.format(bid))))