Liming Liang

Assistant Professor of Statistical Genetics

Department of Biostatistics

My research

Our group focuses on developing the computational and statistical tools required for understanding human genetic variation, with a particular focus on complex human disease. We are currently working on the following areas:

(1) Analysis of gene expression and methylation data, particular eQTL/meQTL mapping using both microarray and RNA-seq data, gene expression/methylation network estimation and its association with disease and trait of interest.

(2) New statistical approaches for the analysis of next-generation sequencing data. Ongoing projects include high depth sequencing on ~4000 breast cancer case-control subjects from multiple populations. The goals include fine mapping causal loci responsible for breast cancer risk and developing optimal design for next-generation sequencing studies.

(3) New statistical framework to maximize the utility of multiple related phenotypes and elucidate how genetic and epigenetic variants and their interaction with environmental factors involve in pathogenesis of complex diseases and traits.

(4) Statistical model to integrate genome-wide eQTL/meQTL data with genome-wide association studies.

We are currently part of several large genetic studies, including the 1000 Genomes Project (www.1000genomes.org), genome-wide association studies for type-2 diabetes and related phenotypes and biomarkers, childhood asthma, atopic dermatitis, colorectal cancer,  melanoma, global gene expression and methylation.

I am still maintaining my research website at CSG at the University of Michigan.

Education

PhD, Biostatistics with Dr. Gonçalo Abecasis at the University of Michigan, Ann Arbor, 2009