Research
Scalable statistical methods for complex traits in large-scale biological data.
My research focuses on statistical genomics and the development of scalable methods for analyzing complex traits in large-scale biological data. My overall goal is to develop broadly useful statistical tools that advance biomedical research, precision health, and agricultural improvement.
Genome-wide association studies
Efficient methods for GWAS, including multi-trait analysis, longitudinal analysis, gene–environment interaction analysis, and epistatic interaction analysis.
Genetic subtype identification
Quantifying the genetic separability of disease subtypes to reveal how genetically distinct subtypes are, identifying potential genetic subtypes, and dissecting subtype-specific genetic architecture.
Integrative multi-omics analysis
Integrating whole-genome sequencing, transcriptomics, proteomics, methylomics, and functional genomics data to identify functional genes and biological mechanisms.
Quantitative genetics & genomic selection
Quantitative genetics, genetic evaluation, and genomic selection in livestock, particularly dairy cattle and pigs.