Clair3-RNA: a deep learning-based small variant caller for long-read RNA sequencing data.

ABSTRACT: Variant calling with long-read RNA sequencing (lrRNA-seq) helps to analyze full-length isoforms and gene expression but is complicated by high error rates, transcript diversity, RNA editing events, etc. Here, we propose Clair3-RNA, the first deep learning-based variant caller tailored for lrRNA-seq data. Building upon Clair series' pipelines, Clair3-RNA enhances lrRNA-seq variant calling using optimized techniques, such as uneven coverage normalization, refined training data, editing site discovery, and haplotype phasing to enhance performance. Clair3-RNA supports various platforms, including PacBio, ONT complementary DNA sequencing (cDNA), and ONT direct RNA sequencing (dRNA). Clair3-RNA achieved a ~ 91% SNP F1-score on the ONT platform using the latest ONT SQK-RNA004 kit (dRNA004) and a 

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC12748580 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature