About me

Hi, I’m Dongyuan, Ph.D. candidate in Bioinformatics Interdepartmental Graduate Program, at University of California, Los Angeles (UCLA). I am under supervision of Dr. Jingyi Jessica Li from Department of Statistics & Data Science. Previously, I received Master of Science in Computational Biology & Quantitative Genetics from Department of Biostatistcs, Harvard T.H. Chan School of Public Health, under supervision of Dr. Rafael Irizarry. I obtained Bachelor of Science in Biological Science from Fudan University, Shanghai, China.

I am on the job market this year!

My research focuses on enhancing statistical rigor in analyzing high-dimensional single-cell and spatial genomics. Some of my major works include:

1. Probabilistic generative models of high-dimensional single-cell and spatial multi-omics data. I develped scDesign3, an “all-in-one” multimodal single-cell and spatial omics simulator which summarizes the input real dataset into a parametric model. I also contributed to the development of scReadSim, a single-cell RNA-seq and ATAC-seq read simulator, and scDesign2, the predecessor of scDesign3.
2. Differential expression (DE) test and false discovery rate (FDR) control based on inferred variables. We developed ClusterDE, a post-clustering DE method controlling FDR under “double dipping (i.e., first clustering then DE between clusters)”. Previously, I developed PseudotimeDE, a DE method for testing gene changes along cell pseudotime accounting for the uncertainty of pseudotime.
3. Informative genes/cells selection in large-scale scRNA-seq data. We developed scPNMF, an informative gene selection method for selecting only a small number of genes. We also developed scSampler, a diveristy-preserving cell subsampling method for large datasets.