Our group focuses on the development and application of statistical methods and computational tools for high-dimensional "omics" data, arising from modern high-throughput technologies. Our current research interests include developing novel methods for integrating functional information in genetic association studies, meta-analysis for sequencing studies, and analysis of microbiome & metagenomic data.
News
08/27/2025 Our team has been awarded an R01 grant from the National Institute of Allergy and Infectious Diseases (NIAID) to develop novel statistical methods for microbiome data analysis.
7/31/2025 Our Melody paper has been accepted in Genome Biology. Good job, Zhou! Melody is a powerful method for meta-analysis of microbiome association studies, enabling the discovery of generalizable microbial signatures. The method has been implemented in the miMeta R package.
01/12/2025 Qilin (Kirin) Hong won Early Career Award by ASA Section on Statistics in Epidemiology for his paper, "A marginal regression model for longitudinal compositional counts with application to microbiome data". Congrats, Kirin!
05/27/2024 Zhoujingpeng Wei won NESS Student Paper Awards. Congrats, Weizhou!