Add ML predictor #1303
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Add ML predictor #1303
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Fix IndexError: string index out of range in reference proteome similarity step
Improve handling of inframe indels in repetitive regions
…ng to a shared variable
… unnecessary usage
Ensure that prediction_algorithms list gets copied so it's not pointing to a shared block variable
Update --top-score-metric2 parameter help text for clarity and remove unnecessary usage (hotfix base)
Fix per-allele counts in the aggregated report
…topes/filtered file
…_epitopres/filtered file as an input_tsv
Fix a few bugs where standalone commands don't work with all_epitopes/filtered TSVs
Update example and demo data for 5.5.4 release
- Updated _resolve_artifact_paths() to use numpy126 versions of model artifacts - Added numpy126 model artifacts: rf_downsample_model_numpy126.pkl, trained_imputer_numpy126.joblib, label_encoders_numpy126.pkl - Ensures compatibility with numpy 1.26 and pvactools_ml_integration environment
- Resolved conflicts by accepting master's version for test data files - Preserved ML predictor numpy126 artifacts and updated ml_predictor.py - Successfully integrated latest pVACtools updates with ML model compatibility
Folowing changes was just added to make the test script for ml_predictor to work - Add is_preferred_transcript() function - Add transcript_prioritization_strategy() function - Add pandas import - Resolves import errors in ML predictor tests
- Remove label_encoders.pkl (old version) - Remove rf_downsample_model.pkl (old version) - Remove trained_imputer.joblib (old version) - Keep only numpy126-compatible artifacts for ML predictor integration
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This project aims to create a ML model for facilitating the ITB decisions for peptide vaccines. The model takes the following as input and predicts decisions in the "Evaluation" column in the pvacview file: