| ---
|
| license: mit
|
| task_categories:
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| - text-classification
|
| tags:
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| - peptide
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| - mhc
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| - hla
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| - binding-prediction
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| - immunology
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| size_categories:
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| - 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
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|
|
| 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
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|
|
| - `train.csv`: Training data
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| - `id_test.csv`: In-distribution test data
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|
|
| ### Data Format
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|
|
| Each CSV file contains the following columns:
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|
|
| | Column | Type | Description |
|
| |--------|------|-------------|
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| | peptide | string | Peptide amino acid sequence |
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| | HLA | string | HLA allele (standardized format: A*02:01) |
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| | label | int | Binary binding label (0=non-binder, 1=binder) |
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| | length | int | Peptide length (8-14 amino acids) |
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| | HLA_sequence | string | HLA pseudo-sequence |
|
|
|
| ### Dataset Statistics
|
|
|
| **Training Set:**
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| - Total samples: 1683280
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| - Label type: Binary (0/1)
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| - Positive rate: 18.25% (307201/1683280)
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| - Unique HLAs: 112
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| - Unique peptides: 1481879
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| - Peptide length range: 8-14
|
|
|
| **Test Set (In-Distribution):**
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| - Total samples: 586608
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| - Label type: Binary (0/1)
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| - Positive rate: 14.64% (85876/586608)
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| - Unique HLAs: 112
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| - Unique peptides: 558035
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| - Peptide length range: 8-14
|
|
|
| ## Usage
|
|
|
| ### Load with Pandas
|
|
|
| ```python
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| from huggingface_hub import hf_hub_download
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| import pandas as pd
|
|
|
| # Download files
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| train_file = hf_hub_download(
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| repo_id="YYJMAY/pm-binding",
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| filename="train.csv",
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| repo_type="dataset"
|
| )
|
| test_file = hf_hub_download(
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| repo_id="YYJMAY/pm-binding",
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| filename="id_test.csv",
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| repo_type="dataset"
|
| )
|
|
|
| # Load data
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| train_df = pd.read_csv(train_file)
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| test_df = pd.read_csv(test_file)
|
| ```
|
|
|
| ### Use with SPRINT Framework
|
|
|
| ```python
|
| from sprint.core.dataset_manager import DatasetManager
|
|
|
| manager = DatasetManager()
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| config = {
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| 'hf_repo': 'YYJMAY/pm-binding',
|
| 'files': ['train.csv', 'id_test.csv']
|
| }
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|
|
| 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
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| 2. **HLA Standardization**: Normalized HLA allele names to A*02:01 format
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| 3. **Quality Control**: Removed duplicates and incomplete entries
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| 4. **Column Standardization**: Unified column names and formats
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| 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
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| - **In-Distribution Evaluation**: Testing model performance on similar data distribution as training
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| - **Baseline Comparison**: Standardized data for reproducible benchmarking
|
|
|
| ## Citation
|
|
|
| If you use this dataset, please cite:
|
|
|
| ```bibtex
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| @dataset{pm_dataset_2024,
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| title={PM (Peptide-MHC) Binding Prediction Dataset},
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| author={SPRINT Framework Contributors},
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| year={2024},
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| url={https://huggingface.co/datasets/YYJMAY/pm-binding}
|
| }
|
| ```
|
|
|
| ## License
|
|
|
| MIT License
|
|
|
| ## Contact
|
|
|
| For questions or issues, please refer to the SPRINT framework repository.
|
|
|
