Symphonizing pileup and full-alignment for deep learning-based long-read variant calling

Deep learning-based variant callers are becoming the standard and have achieved superior single nucleotide polymorphisms calling performance using long reads. Here we present Clair3, which leverages two major method categories: pileup calling handles most variant candidates with speed, and full-alig...

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Veröffentlicht in:Nature Computational Science 2022-12, Vol.2 (12), p.797-803
Hauptverfasser: Zheng, Zhenxian, Li, Shumin, Su, Junhao, Leung, Amy Wing-Sze, Lam, Tak-Wah, Luo, Ruibang
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Sprache:eng
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Zusammenfassung:Deep learning-based variant callers are becoming the standard and have achieved superior single nucleotide polymorphisms calling performance using long reads. Here we present Clair3, which leverages two major method categories: pileup calling handles most variant candidates with speed, and full-alignment tackles complicated candidates to maximize precision and recall. Clair3 runs faster than any of the other state-of-the-art variant callers and demonstrates improved performance, especially at lower coverage.
ISSN:2662-8457
2662-8457
DOI:10.1038/s43588-022-00387-x