My lab focuses on developing statistical and computational methods for the analysis of large-scale biomedical data and applying them to study complex diseases. Collaborating with our colleagues, we use cutting-edge technologies including DNA-seq, RNA-seq, methylation, ATAC-seq and single cell sequencing to study human diseases such as childhood asthma and age-related macular degeneration. Chen lab welcomes collaborators and trainees to move science forward. Our lab is generously supported by National Institute of Health, National Science Foundation, University of Pittsburgh and UPMC.
Xu Z, Heidrich-O’Hare E, Chen W, Duerr R. Comprehensive benchmarking of CITE-seq versus DOGMA-seq single cell multimodal omics. .
Yan Q, Forno E, C Celedón J, Chen W. A region-based method for causal mediation analysis of DNA methylation data. .
Yan Q, Ding Y, Weeks DE, Chen W. AMD Genetics: Methods and Analyses for Association, Progression, and Prediction. .
Xin H, Lian Q, Jiang Y, Luo J, Wang X, Erb C, Xu Z, Zhang X, Heidrich-O’Hare E, Yan Q, Duerr RH, Chen K, Chen W. GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing. .
Wang X, Sun Z, Zhang Y, Xu Z, Xin H, Huang H, Duerr RH, Chen K, Ding Y, Chen W. BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data. .