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updated to python3
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dranion committed Aug 23, 2020
1 parent 0631068 commit a5d062f
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Showing 55 changed files with 208 additions and 208 deletions.
14 changes: 7 additions & 7 deletions Makefile
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Original file line number Diff line number Diff line change
Expand Up @@ -45,8 +45,8 @@ help:
@echo "$$help"


python=python2.7
pip=pip2.7
python=python
pip=pip
tests=src/protect/test/unit
extras=

Expand All @@ -55,7 +55,7 @@ normal=\033[0m
red=\033[0;31m

prepare: check_venv
@$(pip) install toil==3.8.0 pytest==2.8.3
@$(pip) install toil pytest

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@drkthomp

drkthomp Nov 28, 2020

no reason to have explicit versioning while still figuring it out.

develop: check_venv
$(pip) install -e .$(extras)
Expand Down Expand Up @@ -107,10 +107,10 @@ clean_pypi:

clean: clean_develop clean_sdist clean_pypi


check_venv:
@$(python) -c 'import sys; sys.exit( int( not hasattr(sys, "real_prefix") ) )' \
|| ( echo "$(red)A virtualenv must be active.$(normal)" ; false )
#always fails, even though in a venv

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@drkthomp

drkthomp Nov 28, 2020

@Dranion

  • Figure out the venv check
#check_venv:
# @$(python) -c 'import sys; sys.exit( int( not hasattr(sys, "real_prefix") ) )' \
# || ( echo "$(red)A virtualenv must be active.$(normal)" ; false )


check_clean_working_copy:
Expand Down
50 changes: 25 additions & 25 deletions attic/ProTECT.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
Program info can be found in the docstring of the main function.
Details can also be obtained by running the script with -h .
"""
from __future__ import print_function


import argparse
import errno
Expand All @@ -33,7 +33,7 @@
import time
from collections import defaultdict, Counter
from multiprocessing import cpu_count
from urlparse import urlparse
from urllib.parse import urlparse

from pysam import Samfile

Expand Down Expand Up @@ -78,7 +78,7 @@ def parse_config_file(job, config_file):
# along with it's parameters.
for groupname, group_params in tool_specific_param_generator(job, conf):
if groupname == 'patient':
if 'patient_id' not in group_params.keys():
if 'patient_id' not in list(group_params.keys()):
raise ParameterError('A patient group is missing the patient_id flag.')
sample_set[group_params['patient_id']] = group_params
elif groupname == 'Universal_Options':
Expand All @@ -104,7 +104,7 @@ def parse_config_file(job, config_file):
raise ParameterError(' The following tools have no arguments in the config file : \n' +
'\n'.join(missing_tools))
# Start a job for each sample in the sample set
for patient_id in sample_set.keys():
for patient_id in list(sample_set.keys()):
job.addFollowOnJobFn(pipeline_launchpad, sample_set[patient_id], univ_options, tool_options)
return None

Expand Down Expand Up @@ -248,7 +248,7 @@ def delete_fastqs(job, fastqs):
+- 'normal_dna': [<JSid for 1.fastq> , <JSid for 2.fastq>]
"""
for fq_type in ['tumor_rna', 'tumor_dna', 'normal_dna']:
for i in xrange(0,2):
for i in range(0,2):
job.fileStore.deleteGlobalFile(fastqs[fq_type][i])
return None

Expand Down Expand Up @@ -727,7 +727,7 @@ def spawn_radia(job, rna_bam, tumor_bam, normal_bam, univ_options, radia_options
'normal_dnai': normal_bam['normal_dna_fix_pg_sorted.bam.bai']}
# Make a dict object to hold the return values for each of the chromosome jobs. Then run radia
# on each chromosome.
chromosomes = [''.join(['chr', str(x)]) for x in range(1, 23) + ['X', 'Y']]
chromosomes = [''.join(['chr', str(x)]) for x in list(range(1, 23)) + ['X', 'Y']]
perchrom_radia = defaultdict()
for chrom in chromosomes:
perchrom_radia[chrom] = job.addChildJobFn(run_radia, bams, univ_options, radia_options,
Expand Down Expand Up @@ -755,11 +755,11 @@ def merge_radia(job, perchrom_rvs):
work_dir = job.fileStore.getLocalTempDir()
# We need to squash the input dict of dicts to a single dict such that it can be passed to
# get_files_from_filestore
input_files = {filename: jsid for perchrom_files in perchrom_rvs.values()
for filename, jsid in perchrom_files.items()}
input_files = {filename: jsid for perchrom_files in list(perchrom_rvs.values())
for filename, jsid in list(perchrom_files.items())}
input_files = get_files_from_filestore(job, input_files, work_dir,
docker=False)
chromosomes = [''.join(['chr', str(x)]) for x in range(1, 23) + ['X', 'Y']]
chromosomes = [''.join(['chr', str(x)]) for x in list(range(1, 23)) + ['X', 'Y']]
with open('/'.join([work_dir, 'radia_calls.vcf']), 'w') as radfile, \
open('/'.join([work_dir, 'radia_filter_passing_calls.vcf']), 'w') as radpassfile:
for chrom in chromosomes:
Expand Down Expand Up @@ -961,7 +961,7 @@ def spawn_mutect(job, tumor_bam, normal_bam, univ_options, mutect_options):
job.fileStore.logToMaster('Running spawn_mutect on %s' % univ_options['patient'])
# Make a dict object to hold the return values for each of the chromosome
# jobs. Then run mutect on each chromosome.
chromosomes = [''.join(['chr', str(x)]) for x in range(1, 23) + ['X', 'Y']]
chromosomes = [''.join(['chr', str(x)]) for x in list(range(1, 23)) + ['X', 'Y']]
perchrom_mutect = defaultdict()
for chrom in chromosomes:
perchrom_mutect[chrom] = job.addChildJobFn(run_mutect, tumor_bam, normal_bam, univ_options,
Expand All @@ -987,10 +987,10 @@ def merge_mutect(job, perchrom_rvs):
work_dir = job.fileStore.getLocalTempDir()
# We need to squash the input dict of dicts to a single dict such that it can be passed to
# get_files_from_filestore
input_files = {filename: jsid for perchrom_files in perchrom_rvs.values()
for filename, jsid in perchrom_files.items()}
input_files = {filename: jsid for perchrom_files in list(perchrom_rvs.values())
for filename, jsid in list(perchrom_files.items())}
input_files = get_files_from_filestore(job, input_files, work_dir, docker=False)
chromosomes = [''.join(['chr', str(x)]) for x in range(1, 23) + ['X', 'Y']]
chromosomes = [''.join(['chr', str(x)]) for x in list(range(1, 23)) + ['X', 'Y']]
with open('/'.join([work_dir, 'mutect_calls.vcf']), 'w') as mutvcf, \
open('/'.join([work_dir, 'mutect_calls.out']), 'w') as mutout, \
open('/'.join([work_dir, 'mutect_passing_calls.vcf']), 'w') as mutpassvcf:
Expand Down Expand Up @@ -1139,7 +1139,7 @@ def run_mutation_aggregator(job, fusion_output, radia_output, mutect_output, ind
input_files.pop('fusion.vcf')
# read files into memory
vcf_file = defaultdict()
mutcallers = input_files.keys()
mutcallers = list(input_files.keys())
with open(''.join([work_dir, '/', univ_options['patient'], '_merged_mutations.vcf']),
'w') as merged_mut_file:
for mut_caller in mutcallers:
Expand Down Expand Up @@ -1571,8 +1571,8 @@ def merge_mhc_peptide_calls(job, antigen_predictions, transgened_files):
mhci_files = get_files_from_filestore(job, mhci_preds, work_dir)
# First split mhcii_preds into prediction files and predictors and maintain keys so we can later
# reference them in pairs
mhcii_predictors = {x: y[1] for x, y in mhcii_preds.items()}
mhcii_files = {x: y[0] for x, y in mhcii_preds.items()}
mhcii_predictors = {x: y[1] for x, y in list(mhcii_preds.items())}
mhcii_files = {x: y[0] for x, y in list(mhcii_preds.items())}
mhcii_files = get_files_from_filestore(job, mhcii_files, work_dir)
# Get peptide files
pept_files = get_files_from_filestore(job, pept_files, work_dir)
Expand All @@ -1584,7 +1584,7 @@ def merge_mhc_peptide_calls(job, antigen_predictions, transgened_files):
pepmap = json.load(mapfile)
# Incorporate peptide names into the merged calls
with open('/'.join([work_dir, 'mhci_merged_files.list']), 'w') as mhci_resfile:
for mhcifile in mhci_files.values():
for mhcifile in list(mhci_files.values()):
with open(mhcifile, 'r') as mf:
for line in mf:
# Skip header lines
Expand All @@ -1605,7 +1605,7 @@ def merge_mhc_peptide_calls(job, antigen_predictions, transgened_files):
# Incorporate peptide names into the merged calls
with open('/'.join([work_dir, 'mhcii_merged_files.list']), 'w') as \
mhcii_resfile:
for mhciifile in mhcii_files.keys():
for mhciifile in list(mhcii_files.keys()):
core_col = None # Variable to hold the column number with the core
if mhcii_predictors[mhciifile] == 'Consensus':
with open(mhcii_files[mhciifile], 'r') as mf:
Expand Down Expand Up @@ -1814,7 +1814,7 @@ def prepare_samples(job, fastqs, univ_options):
'normal_dna_fastq_prefix'}
if set(fastqs.keys()).difference(allowed_samples) != {'patient_id'}:
raise ParameterError('Sample with the following parameters has an error:\n' +
'\n'.join(fastqs.values()))
'\n'.join(list(fastqs.values())))
# For each sample type, check if the prefix is an S3 link or a regular file
# Download S3 files.
for sample_type in ['tumor_dna', 'tumor_rna', 'normal_dna']:
Expand Down Expand Up @@ -1877,7 +1877,7 @@ def get_files_from_filestore(job, files, work_dir, cache=True, docker=False):
work_dir is the location where the file should be stored
cache indiciates whether caching should be used
"""
for name in files.keys():
for name in list(files.keys()):
outfile = job.fileStore.readGlobalFile(files[name], '/'.join([work_dir, name]), cache=cache)
# If the file pointed to a tarball, extract it to WORK_DIR
if tarfile.is_tarfile(outfile) and file_xext(outfile).startswith('.tar'):
Expand Down Expand Up @@ -1924,15 +1924,15 @@ def most_probable_alleles(allele_list):
except KeyError:
all_alleles[allele] = [float(pvalue)]
# If there are less than 2 alleles, report all
if len(all_alleles.keys()) <= 2:
return all_alleles.keys()
if len(list(all_alleles.keys())) <= 2:
return list(all_alleles.keys())
# Else, get the two with most evidence. Evidence is gauged by
# a) How many files (of the 3) thought that Allele was present
# b) In a tie, who has a lower avg p value
# In the lambda function, if 2 alleles have the same number of calls, the sum of the p values is
# a measure of the avg because avg = sum / n and n is equal in both of them.
else:
return sorted(all_alleles.keys(), key=lambda x: \
return sorted(list(all_alleles.keys()), key=lambda x: \
(-len(all_alleles[x]), sum(all_alleles[x])))[0:2]


Expand Down Expand Up @@ -2111,7 +2111,7 @@ def print_mhc_peptide(neoepitope_info, peptides, pepmap, outfile):
"""
allele, pept, pred, core = neoepitope_info
peptide_names = [x for x, y in peptides.items() if pept in y]
peptide_names = [x for x, y in list(peptides.items()) if pept in y]
# For each peptide, append the ensembl gene
for peptide_name in peptide_names:
print(allele, pept, peptide_name, core, '0', pred, pepmap[peptide_name], sep='\t',
Expand Down Expand Up @@ -2514,7 +2514,7 @@ def strip_xext(filepath):
:return str filepath: Path to the file with the compression extension stripped off.
"""
ext_size = len(file_xext(filepath).split('.')) - 1
for i in xrange(0, ext_size):
for i in range(0, ext_size):
filepath = os.path.splitext(filepath)[0]
return filepath

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