Kuan-Hao Chao

This paper introduces SpliceAI2, a deep learning model that improves identification and quantification of splice-altering variants and their effects on transcripts and disease.

T2T-HG002v1.1, a complete diploid HG002 assembly lacking detectable errors over 99.4% of its length, enables genome-based benchmarking of assemblies, sequencing reads, and phased variant calls.

This paper introduces Shorkie, a DNA language model pretrained on fungal genomes that improves gene expression prediction in budding yeast by capturing regulatory motif dynamics and variant effects.

OpenSpliceAI improves SpliceAI by implementing it in PyTorch, enabling faster processing and retraining on non-human species with reduced memory usage.

LiftOn improves genome annotation by integrating DNA and protein alignments, enabling accurate annotation transfer between closely and distantly related species.

Splam improves spliced alignments by accurately predicting splice junctions in DNA, outperforming existing methods like SpliceAI across human and non-human species.

CHESS 3 improves upon previous versions by using better algorithms and filtering to create a more accurate catalog of human genes and transcripts.

The paper introduces Wheelie, an algorithm to check if a graph has Wheeler properties, and presents the WGT toolkit for visualizing and generating Wheeler graphs.

EASTR corrects systematic alignment errors in multi-exon genes by detecting and removing falsely spliced transcripts, improving alignment accuracy across species.

The paper assembles a gapless, reference-quality genome from a Southern Han Chinese individual and identifies gene-level differences compared to a reference genome.

sangeranalyseR provides an interactive R package and Shiny apps for analyzing Sanger sequencing data, offering tools for read trimming, peak detection, and indel analysis.

RNASeqR provides an automated RNA-Seq analysis workflow in R, enabling six-step processing and visualization for comparative transcriptomic studies.