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IR_ISOTOPE_part2.py
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IR_ISOTOPE_part2.py
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"""
@authors: Juan L. Trincado
@email: juanluis.trincado@upf.edu
IR_ISOTOPE.py: get significat intron retention
"""
import csv
from lib.IR.extract_significant_IR import *
from lib.IR.IR_associate_gene_ids import *
from lib.IR.filter_IR import *
from lib.IR.filter_IR_CHESS import *
from lib.IR.generate_random_intronic_positions import *
from lib.IR.get_coverageBed import *
from lib.IR.get_coverageBed_adapter import *
from lib.IR.get_peptide_sequence_RI import *
from lib.IR.select_fasta_candidates import *
from lib.IR.run_netMHC_classI_slurm_part1 import *
from lib.IR.run_netMHC_classI_slurm_part2 import *
from lib.IR.run_netMHCpan_classI_slurm_part1 import *
from lib.IR.run_netMHCpan_classI_slurm_part2 import *
from argparse import ArgumentParser, RawTextHelpFormatter
import argparse
# create logger
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
# create console handler and set level to info
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
# create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# add formatter to ch
ch.setFormatter(formatter)
# add ch to logger
logger.addHandler(ch)
def str2bool(v):
if isinstance(v, bool):
return v
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0'):
return False
else:
raise argparse.ArgumentTypeError('Boolean value expected.')
description = \
"Description: Get IR events\n\n"
parser = ArgumentParser(description=description, formatter_class=RawTextHelpFormatter,
add_help=True)
parser.add_argument("-trans", "--transcript", required=True, help="transcript expression file")
parser.add_argument("-g", "--gtf", required=True, help="gtf annotation")
parser.add_argument("-genome", "--genome", required=True, help="Genome annotation")
parser.add_argument("-HLAclass", "--HLAclass", required=True, help="HLA genotype of the samples")
parser.add_argument("-HLAtypes", "--HLAtypes", required=True, help="HLA alelles recognized by NetMHC")
parser.add_argument("-HLAtypespan", "--HLAtypespan", required=True, help="HLA alelles recognized by NetMHCpan")
parser.add_argument("-netMHC", "--netMHC", required=True, help="netMHC path")
parser.add_argument("-netMHCpan", "--netMHCpan", required=True, help="netMHCpan path")
parser.add_argument("-t", "--thres", required=False, type=int, default=1,
help="Minimum expression to consider an intron")
parser.add_argument("-mosea", "--mosea", required=True, help="MoSEA path")
parser.add_argument("-mxfinder", "--mxfinder", required=True, help="MxFinder path")
parser.add_argument("-o", "--output", required=True, help="Output path")
parser.add_argument("--username", required=True, help="Cluster user name")
parser.add_argument("--tumor_specific", type=str2bool, nargs='?', const=True, default=False,
help="Tumor specific mode")
parser.add_argument("--temp", type=str2bool, nargs='?', const=True, default=False, help="Remove temp files")
parser.add_argument("-c", "--cluster", type=str2bool, nargs='?',const=True, default=False,help="Run in parallel on a cluster")
def main(transcript_expression_path, gtf_path, genome_path, HLAclass_path, HLAtypes_path,
HLAtypes_pan_path, netMHC_path, netMHC_pan_path, threshold,
mosea_path, mxfinder_path, output_path, tumor_specific, remove_temp_files, name_user, cluster):
try:
logger.info("Starting execution IR_ISOTOPE_part2")
# transcript_expression_path = "/projects_rg/SCLC_cohorts/George/tables/iso_tpm_George_Peifer_Rudin_Yokota.tab"
# gtf_path = "/projects_rg/SCLC_cohorts/annotation/Homo_sapiens.GRCh37.75.formatted.only_protein_coding.gtf"
# codons_gtf_path = "/projects_rg/SCLC_cohorts/annotation/Homo_sapiens.GRCh37.75.codons.gtf"
# mosea = "/genomics/users/juanluis/Software/MoSEA-master/mosea.py"
# fasta_genome = "/genomics/users/juanluis/Software/MoSEA-master/test_files/genome/hg19.fa"
# orfs_scripts = "/genomics/users/juanluis/comprna/MxFinder/extract_orfs.py"
# interpro = "/soft/EB_repo/bio/sequence/programs/noarch/interproscan/5.33-72.0/interproscan.sh"
# IUPred = "/projects_rg/SCLC_cohorts/soft/IUPred2A"
# HLAclass_path = "/projects_rg/SCLC_cohorts/tables/PHLAT_summary_ClassI_all_samples.out"
# HLAtypes_path = "/projects_rg/SCLC_cohorts/tables/NetMHC-4.0_HLA_types_accepted.tab"
# HLAtypes_pan_path = "/projects_rg/SCLC_cohorts/tables/NetMHCpan-4.0_HLA_types_accepted.tab"
# netMHC_path = "/projects_rg/SCLC_cohorts/soft/netMHC-4.0/netMHC"
# netMHC_pan_path = "/projects_rg/SCLC_cohorts/soft/netMHCpan-4.0/netMHCpan"
# remove_temp_files = True
# tumor_specific = True
# name_user = "juanluis"
# output_path = "/users/genomics/juanluis/SCLC_cohorts/SCLC/epydoor/IR"
# # ONLY FOR MARVIN
# #python2 = "Python/2.7.14-foss-2017b"
# # ONLY FOR HYDRA
# python2 = "Python/2.7.11"
# 0.1. Create a gtf with only the exon information
dir_path = os.path.dirname(os.path.realpath(__file__))
gtf_path_exon = '{}.{}'.format(gtf_path, "exon")
gtf = pd.read_table(gtf_path, delimiter="\t",header=None,comment="#")
#Get only the information on the exons and on chromosomes from 1 to 22, X and Y
gtf.columns = ['chr', 'type1', 'type2', 'start', 'end', 'dot', 'strand', 'dot2', 'rest_information']
gtf = gtf[gtf['type2'].isin(["exon"])]
gtf = gtf[gtf['chr'].isin(list(range(1,23)) + ["X","Y"])]
#Add the chr suffix
gtf['chr'] = 'chr' + gtf['chr'].astype(str)
#Save the gtf in external file
gtf.to_csv(gtf_path_exon,index=False,header=False,sep ='\t',quoting=csv.QUOTE_NONE)
# 6. Create the folder, if it doesn't exists
logger.info("Part6...")
if not os.path.exists(output_path + "/coverageBed"):
os.makedirs(output_path + "/coverageBed")
# Move all the coverage.sorted files to the created directory
command1="mv "+output_path+"/*coverage_sorted "+output_path + "/coverageBed/"
os.system(command1)
# 7.1. Get the coverage for each exonization
logger.info("Part7.1...")
if(tumor_specific):
output_path_filtered2 = output_path + "/IR_expressed_genes_filtered2.tab"
else:
output_path_filtered2 = output_path + "/IR_expressed_genes.tab"
get_coverageBed_adapter(output_path_filtered2, output_path + "/random_introns.bed",output_path + "/coverageBed", output_path, name_user, cluster)
# 7.2. Assemble all pieces into one single file
logger.info("Part7.2...")
command2="awk 'FNR==1 && NR!=1{next;}{print}' "+output_path+"/get_coverageBed_*.tab > "+output_path+"/IR_coverage.tab"
os.system(command2)
# 7.3. Get the introns with a significant p_value
logger.info("Part7.3...")
command3="head -n1 "+output_path+"/IR_coverage.tab > "+output_path+"/IR_significant_introns.tab; " \
"awk '{ if ($7 <= 0.05 && $6 > 0) print }' "+output_path+"/IR_coverage.tab >> "+output_path+"/IR_significant_introns.tab"
os.system(command3)
# 8. Get the peptide sequence associated
logger.info("Part8...")
get_peptide_sequence(output_path + "/IR_significant_introns.tab", transcript_expression_path, gtf_path,
output_path + "/IR_peptide_sequence.fa", output_path + "/IR_fasta_sequence.fa",
output_path + "/IR_ORF.tab", output_path + "/IR_ORF_sequences.tab", mosea_path,
genome_path, mxfinder_path, remove_temp_files)
# 9. Filter the significant results
logger.info("Part9...")
dir_path = os.path.dirname(os.path.realpath(__file__))
command4="Rscript "+dir_path+"/lib/IR/filter_results.R "+output_path + "/IR_ORF.tab"+" "+ \
output_path + "/IR_ORF_filtered.tab " + str(threshold) + " "+ output_path + "/IR_ORF_filtered_peptide_change.tab"
os.system(command4)
# 10. Select the fasta candidates for being run to the epitope analysis
logger.info("Part10...")
#Create the folder, if it doesn't exists
if not os.path.exists(output_path + "/IR_fasta_files"):
os.makedirs(output_path + "/IR_fasta_files")
select_fasta_candidates(output_path + "/IR_ORF_filtered_peptide_change.tab", output_path + "/IR_peptide_sequence.fa", output_path + "/IR_peptide_sequence_filtered.fa", output_path + "/IR_fasta_files")
#11. Run netMHC-4.0_part1
logger.info("Part11...")
if not os.path.exists(output_path + "/IR_NetMHC-4.0_files"):
os.makedirs(output_path + "/IR_NetMHC-4.0_files")
run_netMHC_classI_slurm_part1(output_path + "/IR_ORF_filtered_peptide_change.tab", HLAclass_path, HLAtypes_path,
output_path + "/IR_fasta_files",output_path + "/IR_NetMHC-4.0_files", output_path + "/IR_NetMHC-4.0_neoantigens_type_gained.tab",
output_path + "/IR_NetMHC-4.0_neoantigens_type_gained_all.tab", output_path + "/IR_NetMHC-4.0_neoantigens_type_lost.tab",
output_path + "/IR_NetMHC-4.0_neoantigens_type_lost_all.tab", output_path + "/IR_NetMHC-4.0_junctions_ORF_neoantigens.tab",
netMHC_path, cluster)
#12. Run netMHCpan-4.0_part1
logger.info("Part12...")
if not os.path.exists(output_path + "/IR_NetMHCpan-4.0_files"):
os.makedirs(output_path + "/IR_NetMHCpan-4.0_files")
run_netMHCpan_classI_slurm_part1(output_path + "/IR_ORF_filtered_peptide_change.tab", HLAclass_path, HLAtypes_pan_path,
output_path + "/IR_fasta_files",output_path + "/IR_NetMHCpan-4.0_files", output_path + "/IR_NetMHCpan-4.0_neoantigens_type_gained.tab",
output_path + "/IR_NetMHCpan-4.0_neoantigens_type_gained_all.tab", output_path + "/IR_NetMHCpan-4.0_neoantigens_type_lost.tab",
output_path + "/IR_NetMHCpan-4.0_neoantigens_type_lost_all.tab", output_path + "/IR_NetMHCpan-4.0_junctions_ORF_neoantigens.tab",
netMHC_pan_path, cluster)
exit(0)
except Exception as error:
logger.error('ERROR: ' + repr(error))
logger.error("Aborting execution")
sys.exit(1)
if __name__ == '__main__':
args = parser.parse_args()
main(args.transcript,args.gtf,args.genome,args.HLAclass,args.HLAtypes,args.HLAtypespan,
args.netMHC,args.netMHCpan,args.thres,args.mosea,args.mxfinder,args.output,args.tumor_specific,
args.temp,args.username,args.cluster)
# main("/home/trincadojl/Projects/SCLC/Smart/data/iso_tpm.txt",
# "/home/trincadojl/Projects/SCLC/Smart/annotation/Homo_sapiens.GRCh37.75.gtf",
# "/media/trincadojl/data/Projects/annotation/hg19.fa",
# "/home/trincadojl/Projects/SCLC/Smart/data/PHLAT_summary_ClassI.out",
# "/home/trincadojl/Projects/SCLC/Smart/data/NetMHC-4.0_HLA_types_accepted.tab",
# "/home/trincadojl/Projects/SCLC/Smart/data/NetMHCpan-4.0_HLA_types_accepted.tab",
# "/home/trincadojl/Software/netMHC-4.0/netMHC",
# "/home/trincadojl/Software/netMHCpan-4.0/netMHCpan",
# 1,
# "/home/trincadojl/Software/MoSEA",
# "/home/trincadojl/Software/MxFinder",
# "/home/trincadojl/Projects/SCLC/Smart/test_ISOTOPE/IR",
# False,
# False,
# "juanluis",
# False)