def output(self):
sample_name = pfn(self.sampleID, 'sample_name')
project_name = pfn(self.sampleID, 'project_name')
return luigi.LocalTarget(
output_fmt.format(
path=base_outpath, PN=project_name, SN=sample_name) + '.sam')
def run(self):
sample_name = pfn(self.PE1, 'sample_name')
project_name = pfn(self.PE1, 'project_name')
log_name = '{base}/{PN}_result/trim_result/{SN}_trimed.log'.format(
base=base_outpath, PN=project_name, SN=sample_name)
if not os.path.isdir('{base}/{PN}_result/trim_result'.format(
base=base_outpath, PN=project_name)):
os.makedirs('{base}/{PN}_result/trim_result'.format(
base=base_outpath, PN=project_name))
input1 = self.PE1
input2 = self.PE2
if input2:
cmdline = "java -jar ~/tools/Trimmomatic-0.36/trimmomatic-0.36.jar PE -threads 20 {base_in}/{input1}.fastq.gz {base_in}/{input2}.fastq.gz -trimlog {output} {base_out}/{input1}.clean.fq.gz {base_out}/{input1}.unpaired.fq.gz {base_out}/{input2}.clean.fq.gz {base_out}/{input2}.unpaired.fq.gz ILLUMINACLIP:/home/liaoth/tools/Trimmomatic-0.36/adapters/TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:50".format(
input1=input1,
input2=input2,
base_in=base_inpath,
base_out=os.path.dirname(log_name),
output=log_name)
os.system(cmdline)
record_cmdline(cmdline)
else:
cmdline = "java -jar ~/tools/Trimmomatic-0.36/trimmomatic-0.36.jar SE -threads 20 {base_in}/{input1}.fastq.gz -trimlog {output} {base_out}/{input1}.clean.fq.gz ILLUMINACLIP:/home/liaoth/tools/Trimmomatic-0.36/adapters/TruSeq3-SE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36".format(
input1=input1,
base_in=base_inpath,
base_out=os.path.dirname(log_name),
output=log_name)
os.system(cmdline)
record_cmdline(cmdline)
def run(self):
sampleIDs = self.sample_IDs.split(',')
output_dir = self.output().path.rpartition('/')[0]
if os.path.isdir(output_dir) != True:
os.makedirs(output_dir)
if pfn(sampleIDs[0], 'mt2_for') == NORMAL_SIG:
input_normal = self.input()[0].path
input_tumor = self.input()[1].path
elif pfn(sampleIDs[0], 'mt2_for') == TUMOR_SIG:
input_normal = self.input()[1].path
input_tumor = self.input()[0].path
else:
input_tumor = ''
input_normal = ''
prefix = self.output().path.rpartition('.bam')[0]
cmdline = '''java -Xmx10g -jar ~/tools/GenomeAnalysisTK-3.6/GenomeAnalysisTK.jar -T MuTect2 --allSitePLs -R {REF} --cosmic {cosmic} --dbsnp {db_snp} --input_file:normal {input_normal} --input_file:tumor {input_tumor} --out {prefix}.vcf --bamOutput {prefix}.bam --log_to_file {prefix}.log'''.format(
REF=REF_file_path,
cosmic=cos_snp,
db_snp=db_snp,
input_tumor=input_tumor,
input_normal=input_normal,
prefix=prefix)
os.system(cmdline)
record_cmdline(cmdline)
def output(self):
Project_ID = pfn(self.sample_NT, 'project_name')
sample_name = pfn(self.sample_NT, 'sample_name')
output_path = somatic_single_output_fmt.format(
path=base_outpath, PN=Project_ID, SN=sample_name) + '.mt2.bam'
return luigi.LocalTarget(output_path)
def output(self):
sampleIDs = self.sample_IDs.split(',')
Project_ID = pfn(sampleIDs[0], 'project_name')
pair_name = pfn(sampleIDs[0], 'pair_name')
output_path = somatic_pair_output_fmt.format(
path=base_outpath, PN=Project_ID, PairN=pair_name) + '.mt2.bam'
return luigi.LocalTarget(output_path)
def run(self):
input1 = self.input()[0].path
mt2_id = pfn(self.sample_NT, 'mt2_for')
prefix = self.output().path.rpartition('.bam')[0]
output_dir = self.output().path.rpartition('/')[0]
if os.path.isdir(output_dir) != True:
os.makedirs(output_dir)
if mt2_id == NORMAL_SIG:
cmdline = '''java -Xmx10g -jar ~/tools/GenomeAnalysisTK-3.6/GenomeAnalysisTK.jar -T MuTect2 --allSitePLs --artifact_detection_mode -R {REF} --cosmic {cosmic} --dbsnp {db_snp} --input_file:tumor {input_tumor} --out {prefix}.vcf --bamOutput {prefix}.bam --log_to_file {prefix}.log '''.format(
REF=REF_file_path,
cosmic=cos_snp,
db_snp=db_snp,
input_tumor=input1,
prefix=prefix)
os.system(cmdline)
record_cmdline(cmdline)
# Normal only
else:
cmdline = '''java -Xmx10g -jar ~/tools/GenomeAnalysisTK-3.6/GenomeAnalysisTK.jar -T MuTect2 --allSitePLs --artifact_detection_mode -R {REF} --cosmic {cosmic} --dbsnp {db_snp} --input_file:tumor {input_tumor} --out {prefix}.vcf --bamOutput {prefix}.bam --log_to_file {prefix}.log --tumor_lod 4 '''.format(
REF=REF_file_path,
cosmic=cos_snp,
db_snp=db_snp,
input_tumor=input1,
prefix=prefix)
os.system(cmdline)
record_cmdline(cmdline)
def requires(self):
samples_IDs = str(self.x).split(',')
pair_bucket = defaultdict(list)
for _x in samples_IDs:
pair_bucket[pfn(_x, 'pair_name')].append(_x)
adjust_multiple = []
for each in pair_bucket.keys():
if len(pair_bucket[each]) > 2:
tmp = pair_bucket[each]
only_normal = [
_ for _ in tmp if pfn(_, 'mt2_for') == NORMAL_SIG
][0]
for _each in tmp:
if pfn(_each, 'mt2_for') == TUMOR_SIG and pfn(
_each, 'sample_name').replace(TUMOR_SIG,
'') != each:
adjust_multiple.append(
(pfn(_each, 'sample_name').replace(TUMOR_SIG, ''),
[only_normal, _each]))
elif pfn(_each, 'mt2_for') == TUMOR_SIG and pfn(
_each, 'sample_name').replace(TUMOR_SIG,
'') == each:
adjust_multiple.append((each, [only_normal, _each]))
pair_bucket.update(dict(adjust_multiple))
global pair_bucket
###{'XK-2': ['XK-2T_S20', 'XK-2W_S17'],'XK-8': ['XK-8T_S21', 'XK-8W_S18']}
samples_IDs += [_x for _x in pair_bucket.keys()]
if debug_:
import pdb
pdb.set_trace()
for i in samples_IDs:
yield Annovar2(sample_ID=i)
def output(self):
sampleIDs = self.sample_IDs.split(',')
Project_ID = pfn(sampleIDs[0], 'project_name')
pair_name = [
k for k, v in pair_bucket.items() if set(v) == set(sampleIDs)
][0]
output_path = somatic_pair_output_fmt.format(
path=base_outpath, PN=Project_ID, PairN=pair_name) + '.mt2.bam'
return luigi.LocalTarget(output_path)
def formatter_output(args):
val = ''
if ',' in args:
arg_List = args.split(',')
parsed_name = []
for val in arg_List:
parsed_name.append(pfn(PE1_fmt.format(input=val), 'all'))
else:
val = args
parsed_name = pfn(PE1_fmt.format(input=val), 'all')
if not self_adjust_fn:
fq_file = PE1_fmt.format(input=val)
else:
input_list = glob.glob(base_inpath + '/*' + val + '*')
if filter_str:
input_list = [
_i.replace(fq_suffix, '') for _i in input_list
if filter_str not in _i
]
fq_file = input_list[0]
if debug_:
import pdb
pdb.set_trace()
output = """Current Variants: Please make sure your variants is right.\n\n
Input path: {b_i}
output path: {b_o}
Sig represent NORMAL: {sig_n}
Sig represent TUMOR: {sig_T}
Pair file format: {pe_fmt}
input_fastq_file example:{fq}\n
One of args filename parsed: {parsed_result}""".format(
b_i=base_inpath,
b_o=base_outpath,
sig_n=NORMAL_SIG,
sig_T=TUMOR_SIG,
pe_fmt=PE1_fmt,
fq=fq_file,
parsed_result=str(parsed_name))
return output
def requires(self):
samples_IDs = str(self.x).split(',')
pair_bucket = defaultdict(list)
for _x in samples_IDs:
pair_bucket[pfn(_x, 'pair_name')].append(_x)
global pair_bucket
###{'XK-2': ['XK-2T_S20', 'XK-2W_S17'],'XK-8': ['XK-8T_S21', 'XK-8W_S18']}
samples_IDs += [_x for _x in pair_bucket.keys()]
for i in samples_IDs:
yield Annovar2(sample_ID=i)
def run(self):
sample_name = pfn(self.PE1, 'sample_name')
project_name = pfn(self.PE1, 'project_name')
trim_r_path = trim_fmt.format(base=base_outpath, PN=project_name)
log_name = os.path.join(trim_r_path, '%s_trimed.log' % sample_name)
if not os.path.isdir(trim_r_path):
os.makedirs(trim_r_path)
input1 = self.PE1
input2 = self.PE2
output1 = PE1_fmt.format(input=pfn(self.PE1, 'sample_name'))
output2 = PE2_fmt.format(input=pfn(self.PE2, 'sample_name'))
if input2:
cmdline = "java -jar {trimmomatic_jar} PE -threads 20 {base_in}/{input1}{fq_suffix} {base_in}/{input2}{fq_suffix} -trimlog {output} {base_out}/{output1}.clean.fq.gz {base_out}/{output1}.unpaired.fq.gz {base_out}/{output2}.clean.fq.gz {base_out}/{output2}.unpaired.fq.gz ILLUMINACLIP:{trimmomatic_jar_dir}/adapters/TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:50".format(
trimmomatic_jar=trimmomatic_jar,
trimmomatic_jar_dir=os.path.dirname(trimmomatic_jar),
input1=input1,
input2=input2,
base_in=base_inpath,
base_out=os.path.dirname(log_name),
output1=output1,
output2=output2,
fq_suffix=fq_suffix,
output=log_name)
os.system(cmdline)
record_cmdline(cmdline)
else:
cmdline = "java -jar {trimmomatic_jar} SE -threads 20 {base_in}/{input1}{fq_suffix} -trimlog {output} {base_out}/{input1}.clean.fq.gz ILLUMINACLIP:{trimmomatic_jar_dir}/adapters/TruSeq3-SE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36".format(
trimmomatic_jar=trimmomatic_jar,
trimmomatic_jar_dir=os.path.dirname(trimmomatic_jar),
input1=input1,
base_in=base_inpath,
base_out=os.path.dirname(log_name),
fq_suffix=fq_suffix,
output=log_name)
os.system(cmdline)
record_cmdline(cmdline)
def run(self):
sample_name = pfn(self.sampleID, 'sample_name')
project_name = pfn(self.sampleID, 'project_name')
if Pair_data:
input1 = self.input().path
input2 = self.input().path.replace(R1_INDICATOR, R2_INDICATOR)
if not os.path.isdir(
output_dir.format(
path=base_outpath, PN=project_name, SN=sample_name)):
os.makedirs(
output_dir.format(path=base_outpath,
PN=project_name,
SN=sample_name))
cmdline = "bwa mem -M -t 20 -k 19 -R '@RG\\tID:{SN}\\tSM:{SN}\\tPL:illumina\\tLB:lib1\\tPU:L001' {REF} {i1} {i2} > {o}".format(
SN=sample_name,
REF=REF_file_path,
i1=input1,
i2=input2,
o=self.output().path)
os.system(cmdline)
record_cmdline(cmdline)
else:
input1 = self.input().path
if not os.path.isdir(
output_dir.format(
path=base_outpath, PN=project_name, SN=sample_name)):
os.makedirs(
output_dir.format(path=base_outpath,
PN=project_name,
SN=sample_name))
cmdline = "bwa mem -M -t 20 -k 19 -R '@RG\\tID:{SN}\\tSM:{SN}\\tPL:illumina\\tLB:lib1\\tPU:L001' {REF} {i1} > {o}".format(
SN=sample_name,
REF=REF_file_path,
i1=input1,
o=self.output().path)
os.system(cmdline)
record_cmdline(cmdline)
def run(self):
input1 = self.input()[0].path
mt2_id = pfn(self.sample_NT, 'mt2_for')
prefix = self.output().path.rpartition('.bam')[0]
output_dir = self.output().path.rpartition('/')[0]
if os.path.isdir(output_dir) != True:
os.makedirs(output_dir)
if bed_file_path:
suffix_str = " --intervals %s" % bed_file_path
else:
suffix_str = ''
if mt2_id == NORMAL_SIG:
cmdline = "{gatk} Mutect2 --java-options '-Xmx20g' --native-pair-hmm-threads 20 --reference {REF} -I {input_tumor} -tumor {T_name} --dbsnp {db_snp} --seconds-between-progress-updates 60 --all-site-pls -stand-call-conf 10 -A Coverage -A DepthPerAlleleBySample -A FisherStrand -A BaseQuality -A QualByDepth -A RMSMappingQuality -A MappingQualityRankSumTest -A ReadPosRankSumTest -A ChromosomeCounts --all-site-pls true --output {prefix}.vcf -bamout {prefix}.bam".format(
gatk=gatk_pro,
REF=REF_file_path,
db_snp=db_snp,
input_tumor=input1,
prefix=prefix,
T_name=pfn(self.sample_NT, 'sample_name')) + suffix_str
os.system(cmdline)
record_cmdline(cmdline)
# Normal only
else:
cmdline = "{gatk} Mutect2 --java-options '-Xmx20g' --native-pair-hmm-threads 20 --reference {REF} -I {input_tumor} -tumor {T_name} --dbsnp {db_snp} --seconds-between-progress-updates 60 --all-site-pls -stand-call-conf 10 -A Coverage -A DepthPerAlleleBySample -A FisherStrand -A BaseQuality -A QualByDepth -A RMSMappingQuality -A MappingQualityRankSumTest -A ReadPosRankSumTest -A ChromosomeCounts --all-site-pls true --output {prefix}.vcf -bamout {prefix}.bam --tumor-lod-to-emit 4".format(
gatk=gatk_pro,
REF=REF_file_path,
db_snp=db_snp,
input_tumor=input1,
prefix=prefix,
T_name=pfn(self.sample_NT, 'sample_name')) + suffix_str
os.system(cmdline)
record_cmdline(cmdline)
def run(self):
sampleIDs = self.sample_IDs.split(',')
output_dir = self.output().path.rpartition('/')[0]
if os.path.isdir(output_dir) != True:
os.makedirs(output_dir)
input_tumor = ''
input_normal = ''
normal_name = ''
tumor_name = ''
if pfn(sampleIDs[0], 'mt2_for') == NORMAL_SIG:
input_normal = self.input()[0].path
input_tumor = self.input()[1].path
normal_name = pfn(sampleIDs[0], 'sample_name')
tumor_name = pfn(sampleIDs[1], 'sample_name')
elif pfn(sampleIDs[0], 'mt2_for') == TUMOR_SIG:
input_normal = self.input()[1].path
input_tumor = self.input()[0].path
normal_name = pfn(sampleIDs[1], 'sample_name')
tumor_name = pfn(sampleIDs[0], 'sample_name')
prefix = self.output().path.rpartition('.bam')[0]
if bed_file_path:
suffix_str = " --intervals %s" % bed_file_path
else:
suffix_str = ''
cmdline = "{gatk} Mutect2 --java-options '-Xmx20g' --native-pair-hmm-threads 20 --reference {REF} -I {input_normal} -normal {N_name} -I {input_tumor} -tumor {T_name} --dbsnp {db_snp} --seconds-between-progress-updates 60 --all-site-pls -stand-call-conf 10 -A Coverage -A DepthPerAlleleBySample -A FisherStrand -A BaseQuality -A QualByDepth -A RMSMappingQuality -A MappingQualityRankSumTest -A ReadPosRankSumTest -A ChromosomeCounts --all-site-pls true --output {prefix}.vcf -bamout {prefix}.bam".format(
REF=REF_file_path,
cosmic=cos_snp,
db_snp=db_snp,
input_tumor=input_tumor,
input_normal=input_normal,
gatk=gatk_pro,
N_name=normal_name,
T_name=tumor_name,
prefix=prefix) + suffix_str
os.system(cmdline)
record_cmdline(cmdline)
def output(self):
project_name = pfn(self.PE1, 'project_name')
output1 = PE1_fmt.format(input=pfn(self.PE1, 'sample_name'))
return luigi.LocalTarget(
os.path.join(trim_fmt.format(base=base_outpath, PN=project_name),
'/%s.clean.fq.gz' % output1))
def Add_in_vcf_PA(bam_list,
vcf_path,
output_vcf,
fasta_file='/home/liaoth/data/hg19/ucsc.hg19.fasta',
N_sig=NORMAL_SIG,
T_sig=TUMOR_SIG):
"""
receive a vcf file and a related bam. Add coverage from bam into vcf and make it a new field.
For pair analyse vcf.
bam_list order must like [normal one, tumor one]
:param bam: bam path
:param vcf: vcf path or vcf file object.
:return: A new vcf to output.
"""
ori_format2info = ['AF', 'AD']
field1 = "SAD"
field2 = "SAF"
field3 = "PoS"
NT_SIG = [pfn(_bam, 'mt2_for') for _bam in bam_list]
NT_name = [pfn(_bam, 'sample_name') for _bam in bam_list]
if type(vcf_path) == str:
vcf_readed = vcf.Reader(open(vcf_path, 'r'))
else:
try:
vcf_readed = vcf.Reader(fsock=vcf_path)
except:
raise IOError
print 'Wrong vcf, it is a %s' % str(type(vcf_path))
pos_list = parsed_vcf2pos_list(vcf_path)
is_single = False
right_infos = vcf_readed.infos
machine = right_infos.values()[0]
# Modify the info part.
if not is_single:
field1_info = [
field1, '4', 'Integer',
"(REF base count, alt base count). Self cal allele depths from bam file. If there are two pair, it is normal-tumore order."
]
field2_info = [
field2, 'R', 'Float',
"Alt base count divide the total reads number in this pos. Self cal frequency from bam file. If there are two pair, it is normal-tumore order."
]
field3_info = [
field3, '1', 'Integer',
"A field which describe this file is single only analysis or pair analysis. 1 for single analysis, 2 for pair analysis."
]
right_infos[field1] = machine._make(field1_info + [None, None])
right_infos[field2] = machine._make(field2_info + [None, None])
right_infos[field3] = machine._make(field3_info + [None, None])
for ori_format in ori_format2info:
_ori_format_info = vcf_readed.formats[ori_format]._asdict().values(
) + [None, None]
_ori_format_info[
3] += ". If there are two pair, it is normal-tumore order." # fetch ori format value and ID and fix it into length == 6
if ori_format == 'AD':
_ori_format_info[1] = '4'
elif ori_format == 'AF':
_ori_format_info[1] = 'R'
right_infos[ori_format] = machine._make(_ori_format_info)
vcf_readed.infos = right_infos
# Fetch the cov info from bam file, and prepare the writed file.
all_cov_info = special_cal_cov(bam_list, pos_list, fasta_file)
vcf_writer = vcf.Writer(open(output_vcf, 'w'), vcf_readed)
for record in vcf_readed:
if record.is_snp:
query_for = (record.CHROM, record.POS - 1)
buckec_SAD = []
bucket_SAF = []
for ori_format in ori_format2info:
exec 'bucket_%s = []' % ori_format
for sample_call in record.samples:
# it needs to fix the sample and the cov_info order.
sample = str(sample_call.sample)
idx = [
NT_SIG.index(s) for s, n in zip(NT_SIG, NT_name)
if sample == n
][0]
cov_info = all_cov_info[idx][query_for]
ref_base, ref_cov = cov_info[0]
if len(cov_info) > 2:
for n_i in range(1, len(cov_info) - 1):
if cov_info[n_i][0] == record.ALT[0]:
alt_base, alt_cov = cov_info[n_i]
elif len(cov_info) == 1:
alt_base = record.ALT[0]
alt_cov = 0
else:
alt_base, alt_cov = cov_info[1]
### fix the bucket order to normal-tumore order.
if sample == [
n for s, n in zip(NT_SIG, NT_name) if s == N_sig
]:
buckec_SAD.insert(0, int(alt_cov))
buckec_SAD.insert(0, int(ref_cov))
if sum((int(ref_cov), int(alt_cov))) != 0:
bucket_SAF.insert(
0,
round(
float(alt_cov) / sum(
(int(ref_cov), int(alt_cov))), 4))
else:
bucket_SAF.insert(0, 0)
# data = dict(sample_call.data._asdict())
for ori_format in ori_format2info:
if ori_format == 'AD':
exec "bucket_{i}.insert(0,tuple(data['{i}'])[0])".format(
i=ori_format)
exec "bucket_{i}.insert(0,tuple(data['{i}'])[1])".format(
i=ori_format)
else:
exec "bucket_{i}.insert(0,data['{i}'])".format(
i=ori_format)
else:
buckec_SAD += [int(ref_cov), int(alt_cov)]
if sum((int(ref_cov), int(alt_cov))) != 0:
bucket_SAF.append(
round(
float(alt_cov) / sum(
(int(ref_cov), int(alt_cov))), 4))
else:
bucket_SAF.append(0)
# data = dict(sample_call.data._asdict())
for ori_format in ori_format2info:
if ori_format == 'AD':
exec "bucket_{i} += list(data['{i}'])".format(
i=ori_format)
else:
exec "bucket_{i}.append(data['{i}'])".format(
i=ori_format)
record.INFO[field1] = buckec_SAD
record.INFO[field2] = bucket_SAF
record.INFO[field3] = 2
for ori_format in ori_format2info:
exec "record.INFO['{i}'] = bucket_{i}".format(i=ori_format)
vcf_writer.write_record(record)
vcf_writer.close()
def output(self):
project_name = pfn(self.PE1, 'project_name')
return luigi.LocalTarget(
'{base}/{PN}_result/trim_result/{input1}.clean.fq.gz'.format(
base=base_outpath, PN=project_name, input1=self.PE1))