Lei Chen

ClairS: a deep-learning method for long-read somatic small variant calling

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

Client-server interfaces enable efficient agent-driven variant calling

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

Leveraging ONT move table values for signal aware variant calling

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

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: A deep-learning method for long-read tumor-only somatic small variant calling

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: A deep-learning method for long-read mosaic small variant calling

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.

Guess till correct: Gungnir codec enabling high error-tolerance and low-redundancy DNA storage through substantial computing power

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.

Towards a new standard in genomic data privacy: a realization of owner-governance

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