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 = "******"
# 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)
def main():
try:
logger.info("Starting execution IR_epydoor_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 = "******"
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"
# 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)
# 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) 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, codons_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",
output_path + "/IR_Interpro.tab", output_path + "/IR_IUPred.tab",
mosea, fasta_genome, orfs_scripts, interpro, IUPred,
remove_temp_files, python2)
# 9. Filter the significant results
logger.info("Part9...")
dir_path = os.path.dirname(os.path.realpath(__file__))
command4="module load R; Rscript "+dir_path+"/lib/IR/filter_results.R "+output_path + "/IR_ORF.tab"+" "+ \
output_path + "/IR_ORF_filtered.tab" +" "+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_3.tab",
output_path + "/IR_NetMHC-4.0_neoantigens_type_3_all.tab",
output_path + "/IR_NetMHC-4.0_neoantigens_type_2.tab",
output_path + "/IR_NetMHC-4.0_neoantigens_type_2_all.tab",
output_path + "/IR_NetMHC-4.0_junctions_ORF_neoantigens.tab",
netMHC_path)
#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_3.tab",
output_path + "/IR_NetMHCpan-4.0_neoantigens_type_3_all.tab",
output_path + "/IR_NetMHCpan-4.0_neoantigens_type_2.tab",
output_path + "/IR_NetMHCpan-4.0_neoantigens_type_2_all.tab",
output_path + "/IR_NetMHCpan-4.0_junctions_ORF_neoantigens.tab",
netMHC_pan_path)
logger.info(
"Wait until all jobs have finished. Then, go on with part3")
exit(0)
except Exception as error:
logger.error('ERROR: ' + repr(error))
logger.error("Aborting execution")
sys.exit(1)