Hi, my self swetha using topiary, working with TCGA maf file to find the HLA class-I and II core peptide prediction I am getting error please help me to work on this, I want to work with human alleles
command: topiary --maf read.maf --mhc-predictor netMHCIIpan --mhc-alleles "DRB10101" --output-csv epitopes.csv
Namespace(download_reference_genome_data=False, genome=None, ic50_cutoff=None, json_variants=[], maf=['read.maf'], mhc_alleles='DRB10101', mhc_alleles_file=None, mhc_epitope_lengths=None, mhc_peptide_lengths=None, mhc_predictor='netmhciipan', mhc_predictor_models_path=None, mhc_predictor_path=None, only_novel_epitopes=False, output_csv='epitopes.csv', output_csv_sep=',', output_html=None, padding_around_mutation=None, percentile_cutoff=None, print_columns=False, protein_change=[], rename_output_column=None, rna_gene_fpkm_tracking_file=None, rna_min_gene_expression=0.0, rna_min_transcript_expression=0.0, rna_transcript_fpkm_gtf_file=None, rna_transcript_fpkm_tracking_file=None, skip_variant_errors=False, subset_output_columns=None, variant=[], vcf=[], wildtype_ligandome_directory=None)
INFO:mhctools.cli.args:Building MHC binding prediction function for alleles ['HLA-DRA101:01-DRB101:01'] and epitope lengths None
INFO:mhctools.netmhcii_pan:Using NetMHCIIpan 4.0
INFO:mhctools.base_commandline_predictor:Skipping allele DRB5_0108N: The suffix 'N' of 'DRB5*0108N' was not parsed
INFO:mhctools.base_commandline_predictor:Skipping allele BoLA-DRA-DRB30101 BoLA-DRA-DRB30101: Allele has too many parts: DRA-DRB30101 BoLA-DRA-DRB30101
INFO:mhctools.base_commandline_predictor:Skipping allele BoLA-DRA-DRB31101 BoLA-DRA-DRB31101: Allele has too many parts: DRA-DRB31101 BoLA-DRA-DRB31101
INFO:mhctools.base_commandline_predictor:Skipping allele BoLA-DRA-DRB31501 BoLA-DRA-DRB31501: Allele has too many parts: DRA-DRB31501 BoLA-DRA-DRB31501
Traceback (most recent call last):
File "/home/swetha/.local/bin/topiary", line 8, in
sys.exit(main())
File "/home/swetha/.local/lib/python3.8/site-packages/topiary/cli/script.py", line 53, in main
df = predict_epitopes_from_args(args)
File "/home/swetha/.local/lib/python3.8/site-packages/topiary/cli/args.py", line 91, in predict_epitopes_from_args
return predictor.predict_from_variants(
File "/home/swetha/.local/lib/python3.8/site-packages/topiary/predictor.py", line 402, in predict_from_variants
effects = variants.effects(raise_on_error=self.raise_on_error)
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant_collection.py", line 118, in effects
return EffectCollection([
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant_collection.py", line 121, in
for effect in variant.effects(raise_on_error=raise_on_error)
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant.py", line 451, in effects
return predict_variant_effects(
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/effects/effect_prediction.py", line 66, in predict_variant_effects
gene_ids = variant.gene_ids
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant.py", line 422, in gene_ids
self._check_that_genome_has_contig()
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant.py", line 370, in _check_that_genome_has_contig
raise ValueError("Invalid contig name '%s' for reference '%s'" % (
ValueError: Invalid contig name 'chr1' for reference 'GRCh38'
Thanks
swetha
Hi, my self swetha using topiary, working with TCGA maf file to find the HLA class-I and II core peptide prediction I am getting error please help me to work on this, I want to work with human alleles command: topiary --maf read.maf --mhc-predictor netMHCIIpan --mhc-alleles "DRB10101" --output-csv epitopes.csv Namespace(download_reference_genome_data=False, genome=None, ic50_cutoff=None, json_variants=[], maf=['read.maf'], mhc_alleles='DRB10101', mhc_alleles_file=None, mhc_epitope_lengths=None, mhc_peptide_lengths=None, mhc_predictor='netmhciipan', mhc_predictor_models_path=None, mhc_predictor_path=None, only_novel_epitopes=False, output_csv='epitopes.csv', output_csv_sep=',', output_html=None, padding_around_mutation=None, percentile_cutoff=None, print_columns=False, protein_change=[], rename_output_column=None, rna_gene_fpkm_tracking_file=None, rna_min_gene_expression=0.0, rna_min_transcript_expression=0.0, rna_transcript_fpkm_gtf_file=None, rna_transcript_fpkm_tracking_file=None, skip_variant_errors=False, subset_output_columns=None, variant=[], vcf=[], wildtype_ligandome_directory=None) INFO:mhctools.cli.args:Building MHC binding prediction function for alleles ['HLA-DRA101:01-DRB101:01'] and epitope lengths None INFO:mhctools.netmhcii_pan:Using NetMHCIIpan 4.0 INFO:mhctools.base_commandline_predictor:Skipping allele DRB5_0108N: The suffix 'N' of 'DRB5*0108N' was not parsed INFO:mhctools.base_commandline_predictor:Skipping allele BoLA-DRA-DRB30101 BoLA-DRA-DRB30101: Allele has too many parts: DRA-DRB30101 BoLA-DRA-DRB30101 INFO:mhctools.base_commandline_predictor:Skipping allele BoLA-DRA-DRB31101 BoLA-DRA-DRB31101: Allele has too many parts: DRA-DRB31101 BoLA-DRA-DRB31101 INFO:mhctools.base_commandline_predictor:Skipping allele BoLA-DRA-DRB31501 BoLA-DRA-DRB31501: Allele has too many parts: DRA-DRB31501 BoLA-DRA-DRB31501 Traceback (most recent call last): File "/home/swetha/.local/bin/topiary", line 8, in
sys.exit(main())
File "/home/swetha/.local/lib/python3.8/site-packages/topiary/cli/script.py", line 53, in main
df = predict_epitopes_from_args(args)
File "/home/swetha/.local/lib/python3.8/site-packages/topiary/cli/args.py", line 91, in predict_epitopes_from_args
return predictor.predict_from_variants(
File "/home/swetha/.local/lib/python3.8/site-packages/topiary/predictor.py", line 402, in predict_from_variants
effects = variants.effects(raise_on_error=self.raise_on_error)
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant_collection.py", line 118, in effects
return EffectCollection([
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant_collection.py", line 121, in
for effect in variant.effects(raise_on_error=raise_on_error)
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant.py", line 451, in effects
return predict_variant_effects(
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/effects/effect_prediction.py", line 66, in predict_variant_effects
gene_ids = variant.gene_ids
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant.py", line 422, in gene_ids
self._check_that_genome_has_contig()
File "/home/swetha/.local/lib/python3.8/site-packages/varcode/variant.py", line 370, in _check_that_genome_has_contig
raise ValueError("Invalid contig name '%s' for reference '%s'" % (
ValueError: Invalid contig name 'chr1' for reference 'GRCh38'
Thanks
swetha