Article

A systematic assessment of machine learning for structural variant filtering

2026-01-30

Abstract excerpt

<h4>Background</h4> Accurate discrimination of true structural variants (SVs) from artifacts in long-read sequencing data remains a critical bottleneck. Numerous machine learning solutions have been proposed, ranging from classical models using engineered features to advanced deep learning and foundation model interpretability methods. However, a systematic comparison of their performance, efficiency, and practic...

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Literature Corpus work: 8ffb3dc4-a59c-5c53-ac96-714b30039007
DOI: 10.64898/2026.01.27.702059

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