Liangying Yin

This study uses CombGWAS to analyze genetic correlations between psychiatric disorder combinations and cardiovascular disease, identifying shared and unique genetic factors.

CausalCellInfer integrates single-cell RNA-seq with biobank-scale GWAS to identify cell-type-specific disease mechanisms, revealing known and novel biological signals in traits like Type 2 Diabetes and depression.

This paper introduces a Bayesian network framework to estimate direct and indirect causal effects of genes on complex traits using GWAS data and gene expression, showing improved enrichment of known genes and pathways.

This paper introduces a framework integrating GWAS-derived transcriptomes and clinical data to subtype complex diseases, showing improved clustering performance and biological relevance in schizophrenia and cardiovascular risk stratification.