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Datasets:
isalgo
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pmhc_data

Languages:
English
Size:
10M<n<100M
Tags:
immunology
immunopeptidomics
neoantigen
mhc
hla
t-cell
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metadata 
pretty_name: pMHC Data Compendium
license: other
license_name: mixed-upstream
license_link: https://huggingface.co/datasets/isalgo/pmhc_data#licensing
language:
  - en
tags:
  - immunology
  - immunopeptidomics
  - neoantigen
  - mhc
  - hla
  - t-cell
  - cancer-vaccine
  - proteomics
size_categories:
  - 10M<n<100M

pMHC Data Compendium

Harmonized peptide–MHC data for neoantigen scoring: presentation, immunogenicity labels, self/foreign reference peptidomes, expression, and clinical-outcome cohorts. Human and mouse.

Every table here is derived from public sources. Per-file provenance, filtering rules, verified PubMed citations and row-level audits live in the SOURCES.md of each directory — that is the authoritative record, not this page.

Contents

Directory What is in it
pmhc/ Epitope–MHC binding records — the presentation panel (pmhc_full, and pmhc_shortlist at ≥2 references)
immunogenicity/ T-cell immunogenicity corpora: immunogenic vs self ligands and vs non-self, each with an HLA-matched variant; labelled set; HLA population frequencies
neoantigens/ Tested and candidate neoantigens — minigene, epitope-level and per-mutation screens, human and mouse
ligandome/ Foreign and tissue reference peptidomes — viral ligands, pan-viral ORFs, cancer-testis targets, per-tissue corpora
thymus/ Thymic self-peptidome and thymic expression, human and mouse — the central-tolerance reference
expression/ Reference expression, human and mouse, plus a single-pipeline table and mouse protein abundance
proteome/ Human and mouse reference proteomes plus 16 bacterial/viral proteomes for mimicry scans
homology/ Cross-species homology mappings
tcga/ Expressed mutant-peptide–HLA binders across 8,505 donors
hla_loh/ HLA-I loss of heterozygosity and genetic immune escape over 6,319 tumours, with three-caller typing concordance
icb_cohorts/ Harmonized checkpoint-blockade cohorts with outcome
vaccines/ Shipped personalized-vaccine cassettes and their immune monitoring

Formats are mixed by design: gzipped TSV for the large harmonized tables, parquet where the schema is wide or typed, .npz for dense matrices, gzipped FASTA for proteomes.

Shared schema

The immunogenicity tables share one schema:

peptide, mhc_a, mhc_b, mhc_class, mhc_species, source_species, host_species,
assay_type, immunogenicity{1,0,null}, expression, affinity, affinity_wt,
agretopicity, foreignness, validated, dataset_origin, reference_id, n_references

plus patient_id, cancer_type on the neoantigen tables. Canonical columns hold as-reported values only; anything predicted lives in a pred_* column, so affinity is always experimental. affinity units differ by source and MHC alleles are as-reported.

Two things to know before filtering

  • neoantigens/neoag_tested.tsv.gz contains mouse rows labelled as human. 6,186 CEDAR rows carry mouse MHC alleles (H2-Db 1,020, H2-Kb 932, H2-b class I 719, H2-Kd 525, H2-d class II 505, …) while their mhc_species reads HomoSapiens and host_species reads human. SIINFEKL, the canonical H-2Kb ovalbumin epitope, is among them. Filtering that table on mhc_species therefore silently admits mouse pMHC. The defect is upstream and is left unfixed; neoantigens/neoag_tested_mmu.tsv.gz is the correctly-labelled murine set.
  • neoag_tested_{mmu,hsa} overlap neoag_tested.tsv.gz by design — all 2,273 peptides appear in both, since both are IEDB-derived. Dedupe on peptide × MHC when joining.

Loading 

from huggingface_hub import hf_hub_download
import pandas as pd

path = hf_hub_download("isalgo/pmhc_data", "pmhc/pmhc_shortlist.tsv.gz", repo_type="dataset")
df = pd.read_csv(path, sep="\t")

Grab one directory rather than the whole repo:

hf download isalgo/pmhc_data --repo-type dataset --include "neoantigens/*" --local-dir ./pmhc_data

mhcmatch consumes this compendium directly — mhcmatch bootstrap stages the panel and reference tables from here.

Upstream sources

Which table came from which, and under what filtering, is in the SOURCES.md of each directory.

IEDB https://www.iedb.org
CEDAR https://cedar.iedb.org
HLA Ligand Atlas https://hla-ligand-atlas.org
UniProt https://www.uniprot.org
GTEx https://gtexportal.org
Human Protein Atlas https://www.proteinatlas.org
FANTOM5 https://fantom.gsc.riken.jp/5/
UCSC Xena https://xenabrowser.net
GDC / TCGA https://portal.gdc.cancer.gov
ICGC / PCAWG https://dcc.icgc.org
Hartwig Medical Foundation https://www.hartwigmedicalfoundation.nl
Allele Frequency Net Database https://www.allelefrequencies.net
PRIDE https://www.ebi.ac.uk/pride/
MassIVE https://massive.ucsd.edu
GEO https://www.ncbi.nlm.nih.gov/geo/

Licensing

Each upstream source carries its own terms; this compendium redistributes derived, harmonized tables and does not relicense them. Check the SOURCES.md of the directory you are using before redistributing, and cite the primary publications recorded there rather than this repository.