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

Zhenxian ZhengShumin LiJunhao SuAmy Wing-Sze LeungTak-Wah LamRuibang Luo
Published in: Nature computational science (2022)
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.
Keyphrases
  • deep learning
  • machine learning
  • convolutional neural network
  • single molecule