Wanqing Wen

The paper performs single-cell transcriptome-wide association analysis to identify cell-type-specific genetic susceptibility genes for colorectal cancer, finding 546 gene-cell-type associations and 347 candidate susceptibility genes.

The paper uses deconvolution to identify cell-type-specific DNA methylation and gene expression associations with colorectal cancer risk, finding 178 CpG sites and 68 genes across 26 new loci.

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 applies transfer learning to adapt a general-purpose model to a specific domain using limited data, demonstrating improved performance in breast cancer-related tasks.

The paper identifies novel genetic loci associated with blood pressure that interact with sleep duration across multiple ancestries.

The paper identifies 49 novel blood lipid loci associated with gene-sleep interactions in 126,926 individuals across 5 ancestry groups, with gene-short-sleep interactions explaining 4.25% of triglyceride variance.