Junhao Su

The paper uses spatial and single-cell transcriptomics with mitochondrial lineage tracing to uncover fate switching and premetastatic niche formation in osteosarcoma.

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

This study uses mitochondrial variants as barcodes to track clonal dynamics and spatial organization in human hematopoietic organoids.

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.

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

ClusterV-Web provides a user-friendly web interface for analyzing Nanopore long-read data to profile HIV quasispecies and generate drug resistance reports.

This study improves variant calling by integrating Oxford Nanopore and Illumina data using Clair3-MP, showing benefits in difficult genomic regions.

This paper introduces Clair3, a deep learning-based variant caller that combines pile-up and full-alignment methods, achieving faster performance and better accuracy, especially at lower coverage.

This study compares Oxford Nanopore adaptive sequencing and PCR amplicon sequencing for detecting Mycobacterium Tuberculosis in metagenomic samples and calls variants, with an open-source analysis framework.

Clair3-Trio improves variant calling in family trios using Nanopore long-reads with a Trio-to-Trio neural network and a novel loss function.

RENET2 extracts gene-disease associations from full-text articles with higher accuracy than existing tools, identifying 3.72M associations from 1.89M PMC articles.