Jie Ping

scGSCA analyzes single-cell RNA sequencing data to detect differential gene-set co-expression across phenotypes, identifying pathway changes missed by bulk methods.

This study integrates large-scale omics and electronic health records to identify risk proteins and drugs for cancer prevention, finding 101 novel proteins and three drugs associated with reduced colorectal cancer risk.

This study introduces transTF-TWAS, a method that integrates transcription factor-linked trans-located variants into transcriptome-wide association analyses to improve disease risk gene discovery.

The paper identifies 58 risk genes associated with common cancers by linking genetically predicted APA levels to cancer risk using GWAS data.

The paper identifies tissue-specific DNA methylation biomarkers for cancer risk by integrating genome and epigenome data from the GTEx consortium and GWAS data.

This paper introduces sc-UniFrac, a framework to quantify compositional diversity in cell populations across single-cell transcriptome datasets, demonstrating its utility in various applications.