Xuewei Cao

Torino, a reference-free framework for isoform discovery, identifies RNA processing patterns linked to disease risk by analyzing read coverage variation across species and disease states.

This study constructs a bipartite Genotype and Phenotype Network to analyze genetic associations and improve phenome-wide association studies by identifying pleiotropic loci and controlling false discovery rates.

This paper links molecular mechanisms to Alzheimer's disease and aging by integrating neuroimaging endophenotypes with molecular quantitative trait loci.

Spacelink integrates spatial transcriptomics with genetics to identify spatially variable genes linked to disease, showing improved detection power and disease informativeness.

LeafCutter2 identifies and quantifies unproductive splicing events from RNA-seq data, revealing their role in gene regulation and disease, including Alzheimer's.

This paper introduces a Genotype and Phenotype Network (GPN) to improve multiple phenotype association studies by integrating genetic and phenotypic data, showing increased power in detecting pleiotropic loci.

The paper proposes gene selection methods that integrate genetic networks into case-control association studies, showing improved true positive rates for identifying rheumatoid arthritis-related genes.

This paper introduces HCLC-FC, a multivariate method for PheWAS that improves FDR control and identifies significant SNPs in large-scale EMR data.