Department Chair; Professor of Statistics, Adjunct Professor of Molecular BioSciences, Faculty member of NSF-Simons Center for Quantitative Biology
My research interests are in the statistical applications in biology and medical sciences. My recent work concerns developing statistical methods and tools for large-scale, high-dimensional genomic, genetic and human brain mapping data. Some working topics include species number estimation, nucleosome positioning mapping, next-generation sequencing analysis, RNA-seq normalization, Ribo-seq pattern differentiation, fMRI data in human brain mapping and etc. My lab has developed a few software tools that have been frequently used by researchers, including NuPoP (for nucleosome positioning prediction, bioconductor), DegNorm (for degradation normalization for RNA-seq, bioconductor), RiboDiPA (for differential pattern analysis for Ribo-seq data, GitHub ) and SPECIES (for species number estimation, CRAN).
Estimating the species richness by a Poisson-compound Gamma model, Biometrika, 2010, 97(3): 727-740
A base pair resolution map of nucleosome positions in yeast (with Brogaard, Xi and Widom), Nature, 2012, 486: 496–501
A locally convoluted cluster model for nucleosome positioning signals in chemical map (with Xi et al), Journal of American Statistical Association, 2014, 109(505) 48-62
Insights into Nucleosome Organization in Mouse Embryonic Stem Cells through Chemical Mapping (with Voong et al), Cell, 2016, 167(6),1555-1570.e15, highlighted in Nature Reviews Molecular Cell Biology
DegNorm: normalization of generalized transcript degradation improves accuracy in RNA-seq analysis (with Xiong et al), Genome Biology, 2019, 20:75