Lin Jiang

This paper introduces a new statistical method, RUNNER, to detect rare variants associated with complex diseases by comparing observed mutation burdens to predicted baseline values, showing improved power over existing methods.

MCGA identifies schizophrenia susceptibility genes using a multi-strategy framework integrating isoform-level eQTLs, revealing genes enriched in neuronal signaling and drug targets.

This paper introduces a framework to estimate driver tissues of complex diseases by analyzing selective gene expression from GWAS data, finding lung as a driver tissue for rheumatoid arthritis.