Lei Chen

ClairS is a deep-learning method for long-read somatic variant calling that outperforms existing tools on synthetic and short-read datasets.

The paper re-architected a variant caller into a client-server system to improve agent-driven variant calling efficiency and reliability.

Clair3 v2 improves variant calling accuracy for Oxford Nanopore Technologies sequencing by using move table data and dwelling time, achieving higher F1-scores for SNPs and Indels.

Clair3-RNA is a deep learning variant caller for long-read RNA sequencing data that achieves high accuracy in SNP detection across different platforms.

ClairS-TO is a deep-learning method for long-read tumor-only somatic variant calling that outperforms existing tools and works with both long-read and short-read data.

Clair-Mosaic detects mosaic small variants from long-read sequencing data using deep learning, achieving high sensitivity and accuracy in both paired and single-sample modes.

Gungnir is a DNA storage codec that corrects errors through hash matching and biochemical constraints, achieving full data recovery from 20% erroneous bases without redundancy or high-coverage sequencing.

This paper introduces Governome, a blockchain-based genomic data management system that enables owner-governed privacy, encryption, and verifiable data sharing for genomic analysis.