Update branch gnn-explainability with branch main
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added arxiv citations
Added archival DOI Added ray tune dependecy
Inside the utils.data module to we added several functions enhance data preprocessing and reproducibility:
- impute_omics_knn: Imputes missing values (NaNs) in omics data using K-Nearest Neighbors (KNN) imputation.
- normalize_omics: Normalizes omics data using specified methods: standard (Z-score), minmax, or log2.
- set_seed: Sets global random seed for reproducibility across Python, NumPy, and PyTorch.
- impute_omics: Imputes missing values (NaNs) using simple methods: mean, median, or zero.
- beta_to_m: Converts methylation Beta-values to M-values using log2 transformation for statistical analysis.
More commits will follow to develop the respective tests and documentation for these new functions.
Imputation Utils + Tests
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