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metadata
license: mit
task_categories:
  - text-classification
tags:
  - peptide
  - mhc
  - hla
  - binding-prediction
  - immunology
size_categories:
  - n>1M

PM (Peptide-MHC) Binding Prediction Dataset

Dataset Description

This dataset is part of the SPRINT benchmark framework for TCR-pMHC binding prediction. It contains peptide-MHC binding data for training and in-distribution testing of binding prediction models.

Dataset Summary

The PM dataset focuses on peptide-MHC binding prediction without TCR information. It is reorganized and standardized from multiple sources to provide a clean benchmark for PM task evaluation.

Dataset Structure

Files

  • train.csv: Training data
  • id_test.csv: In-distribution test data

Data Format

Each CSV file contains the following columns:

Column Type Description
peptide string Peptide amino acid sequence
HLA string HLA allele (standardized format: A*02:01)
label int Binary binding label (0=non-binder, 1=binder)
length int Peptide length (8-14 amino acids)
HLA_sequence string HLA pseudo-sequence

Dataset Statistics

Training Set:

  • Total samples: 1683280
  • Label type: Binary (0/1)
  • Positive rate: 18.25% (307201/1683280)
  • Unique HLAs: 112
  • Unique peptides: 1481879
  • Peptide length range: 8-14

Test Set (In-Distribution):

  • Total samples: 586608
  • Label type: Binary (0/1)
  • Positive rate: 14.64% (85876/586608)
  • Unique HLAs: 112
  • Unique peptides: 558035
  • Peptide length range: 8-14

Usage

Load with Pandas

from huggingface_hub import hf_hub_download
import pandas as pd

# Download files
train_file = hf_hub_download(
    repo_id="YYJMAY/pm-binding",
    filename="train.csv",
    repo_type="dataset"
)
test_file = hf_hub_download(
    repo_id="YYJMAY/pm-binding",
    filename="id_test.csv",
    repo_type="dataset"
)

# Load data
train_df = pd.read_csv(train_file)
test_df = pd.read_csv(test_file)

Use with SPRINT Framework

from sprint.core.dataset_manager import DatasetManager

manager = DatasetManager()
config = {
    'hf_repo': 'YYJMAY/pm-binding',
    'files': ['train.csv', 'id_test.csv']
}

files = manager.get_dataset('pm', config)

Data Preparation

This dataset was prepared with the following steps:

  1. Source Integration: Combined data from multiple PM binding datasets
  2. HLA Standardization: Normalized HLA allele names to A*02:01 format
  3. Quality Control: Removed duplicates and incomplete entries
  4. Column Standardization: Unified column names and formats
  5. Validation: Checked for data consistency and quality

Tasks

This dataset is designed for:

  • Peptide-MHC Binding Prediction: Predicting binding affinity between peptides and MHC molecules
  • In-Distribution Evaluation: Testing model performance on similar data distribution as training
  • Baseline Comparison: Standardized data for reproducible benchmarking

Citation

If you use this dataset, please cite:

@dataset{pm_dataset_2024,
  title={PM (Peptide-MHC) Binding Prediction Dataset},
  author={SPRINT Framework Contributors},
  year={2024},
  url={https://huggingface.co/datasets/YYJMAY/pm-binding}
}

License

MIT License

Contact

For questions or issues, please refer to the SPRINT framework repository.