The JSB lab is led by the PI, Dr. Jingyi Jessica Li, we have a team of highly motivated graduate students and postdoctoral reserachers. Our research is at the junction of statistics and biology, as our lab name JSB represents. We focus on developing statistical and computational methods motivated by important questions in biomedical sciences and abundant information in big genomic and health related data. On the statistical methodology side, our example interests include association measures, high-dimensional variable selection, and classification metrics. On the biomedical application side, our example interests include next-generation RNA sequencing, comparative genomics, and information flow in the central dogma. We have developed tools such as Clipper, mcRigor, scDEED, and scDesign3, which provide rigorous and interpretable frameworks for controlling false discovery rate, improving the reliability and interpretability of single-cell analyses, mitigating spurious structure in low-dimentional embeddings, and enabling principled benchmarking with realistic single-cell and spatial omics datasets. Our research impact has been recognized by multiple prestigious awards and demonstrated by our many publications in leading scientific and statistical journals.

If you are interested in our research, please check out our YouTube channelTwitter, and Medium.

RECENT NEWS

Jessica Recognized as 2026 Fellows of ASA

Congratulations to Jessica on being named 2026 Fellows of the American Statistical Association (ASA). The ASA Fellow designation is one of the association’s highest honors, recognizing outstanding professional contributions, leadership, and commitment to advancing statistical science. Read the official announcement here

Jessica Named to 2026 Class of ISCB Fellows

Jessica has been named to the 2026 Class of ISCB Fellows by the International Society for Computational Biology. This prestigious honor recognizes her exceptional contributions to biostatistics and computational biology, specifically her groundbreaking leadership in developing statistical frameworks for single-cell and spatial omics data. The 2026 Class will be officially recognized this July at the […]

Jessica receives a new NIH R01 grant

Jessica has received a four-year, $2.4M NIH R01 grant from the National Human Genome Research Institute (NHGRI) to develop statistical methods for generating in-silico controls and pseudo-replicates for single-cell and spatial omics studies. The project will offer a practical way to assess result robustness when true biological replicates cannot be obtained and will provide an […]

JSB Lab moved to Fred Hutchinson Cancer Center

We are excited to announce that the Junction of Statistics & Biology (JSB) Lab has officially relocated to Fred Hutchinson Cancer Center in Seattle, Washington. Starting July 1, 2025, Dr. Jingyi Jessica Li began her new role as Professor and Program Head of the Biostatistics Program at Fred Hutch, where she also holds the Donald […]

SELECTED PUBLICATIONS

91. Song, D., Chen, S., Lee, C., Li, K., Ge, X., and Li, J.J. (2025). Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses. Lecture Notes in Computer Science 15647:400-404; Sankararaman, S., ed.; Springer, Cham. (RECOMB 2025; proceeding)