Xudong Zou

MAAS integrates multimodal scATAC-seq data to identify clinically relevant tumor subpopulations and improve prognostic prediction.

The paper identifies a nuclear RNA degradation code (NRDC) that recognizes transcripts with both a 5' splice site and a poly(A) junction, leading to their degradation and contributing to disease.

This study identifies eRNA-QTLs and susceptibility eRNAs across 23 cancer types, revealing new cancer susceptibility genes through eRNA-based transcriptome-wide association.

This study identifies 413 APA-linked cancer susceptibility genes by integrating GWAS data with APA quantification, showing genetic variants associated with APA explain a large portion of cancer heritability.

xQTLbiolinks is a tool for integrative analysis of molecular QTLs, enabling retrieval, preprocessing, and colocalization with GWAS data to identify disease-risk genes.

DeeReCT-APA quantitatively predicts alternative polyadenylation site usage across genes using a deep learning model, outperforming existing methods in multiple tasks.