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

By Zhenxian Zheng, Shumin Li, J. Su, A. W. Leung, T. Lam, Ruibang Luo. bioRxiv, 2021

352 citations recorded by the source corpus.

Deep learning-based variant callers are becoming the standard and have achieved superior SNP calling performance using long reads. In this paper, we present Clair3, which leveraged the best of two major method categories: pile-up calling handles most variant candidates with speed, and full-alignment tackles complicated candidates to maximize precision and recall. Clair3 ran faster than any of the other state-of-the-art variant callers and performed the best, especially at lower coverage.

Subfields: Artificial Intelligence, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e86d0c73dca317baae08fdb9e9a64a51c42cb47c

Citations in the corpus

• DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing (2023, neutral): “Recent studies showed that both PacBio CCS sequencing and nanopore sequencing can be used for haplotype-aware genome assembly 31 , variant calling 32,33 , and methylation phasing 34 – 37 .”