Article

Accurate Variant Classification in Tumour-Only Genomic Data Using Interpretable Tabular Models

2025-12-12

Abstract excerpt

Recent work has shown that machine learning can provide a reliable tool to classify somatic and rare germline variants in cancer studies where matched-normal samples are not available. Here, we present a workflow that combines an opensource pipeline with three machine-learning models, XGBoost, LightGBM, and TabNet, trained on eight types of features. Our approach substantially enhances the accuracy across all test...

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Literature Corpus work: 38fa3eac-6744-518a-aa77-1db51f60fb77
DOI: 10.64898/2025.12.09.693348

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