Scholarlink

<p>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 ~ 92% SNP F1-score in PacBio Iso-Seq and MAS-Seq for variants with at least 4x coverage. With least 10x coverage and disregarding zygosity, the performance reached a ~ 95% and ~96% F1-score for ONT and PacBio, respectively. After phasing, the performance reached ~97% for ONT and ~98% for PacBio. Across GIAB samples, Clair3-RNA consistently outperformed existing callers and accurately identified RNA editing sites. Clair3-RNA is open-source at (<a href="https://github.com/HKU-BAL/Clair3-RNA">https://github.com/HKU-BAL/Clair3-RNA</a>).</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月22日

查看全文
  • Zhenxian Zheng,
  • Xian Yu,
  • Lei Chen,
  • Yan-Lam Lee,
  • Cheng Xin,
  • Angel On Ki Wong,
  • Miten Jain,
  • Rupesh K. Kesharwani,
  • Fritz J. Sedlazeck,
  • Ruibang Luo

摘要

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 ~ 92% SNP F1-score in PacBio Iso-Seq and MAS-Seq for variants with at least 4x coverage. With least 10x coverage and disregarding zygosity, the performance reached a ~ 95% and ~96% F1-score for ONT and PacBio, respectively. After phasing, the performance reached ~97% for ONT and ~98% for PacBio. Across GIAB samples, Clair3-RNA consistently outperformed existing callers and accurately identified RNA editing sites. Clair3-RNA is open-source at (https://github.com/HKU-BAL/Clair3-RNA).