Ronglai Shen, PhD

Associate Attending Biostatistician

Ronglai Shen, PhD

Office Phone



University of Michigan

Current Research Interests

Dr. Shen’s research interest lies in developing statistical and computational genomics approaches and their applications to translational cancer research. She developed iCluster, a statistical data integration method for defining molecular subtypes of cancer and associated biomarkers across multiple “omic” data types simultaneously characterizing genomic, epigenomic, transcriptomic, and proteomic aberrations in a tumor. Her method has been widely used for integrative cancer subtype analysis in large-scale cancer genome consortium studies including the NCI/NHGRI Cancer Genome Atlas (TCGA) and the Canada-UK Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Working with thoracic oncologists at MSKCC, she applied statistical machine learning approaches for characterizing a patient’s prognostic risk based on the somatic mutational profile of the tumor, and explored the notion of a genomic staging of lung adenocarcinomas (stage IV) in real-world oncology datasets. She is also interested in tumor clonal heterogeneity analysis. Together with Dr. Venkatraman Seshan, she developed FACETS, an allele-specific copy number analysis method that can be used to explore copy number aberrations and clonal heterogeneity within a tumor using whole-genome, whole-exome and targeted capture sequencing data. Her recent research interest also includes a novel investigation of somatic variant richness using statistical methodologies developed in ecology and computational linguistics, a joint work with Dr. Colin Begg and Dr. Saptarshi Chakraborty. This project uses sophisticated statistical tools to extract information from rare variants in existing databases with a view to identifying the site of origin for cancers of unknown primaries and cancers detected from circulating cell-free DNA in the blood.  


Selected peer-reviewed publications:

  1. Chakraborty S, Arora A, Begg CB, Shen R. Using somatic variant richness to mine signals from rare variants in the cancer genome. Nature Communications. 2019 Dec 3;10(1):1-9.
  2. Shen R, Martin A, Ni A, Hellmann M, Arbour KC, Jordan E, Arora A, Ptashkin R, Zehir A, Kris MG, Rudin CM, and Riely GJ. Harnessing Clinical Sequencing Data for Survival Stratification of Patients With Metastatic Lung Adenocarcinomas. JCO precision oncology. 2019 Mar 28;3:1-9.
  3. Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic acids research. 2016 Jun 7;44(16):e131.
  4. Shen R, Wang S, Mo Q. Sparse integrative clustering of multiple omics data sets. The annals of applied statistics. 2013 Apr 9;7(1):269.
  5. Mo Q, Wang S, Seshan VE, Olshen AB, Schultz N, Sander C, Powers RS, Ladanyi M, Shen R. Pattern discovery and cancer gene identification in integrated cancer genomic data. Proceedings of the National Academy of Sciences. 2013 Mar 12;110(11):4245-50.

Visit PubMed for a full listing of Ronglai Shen’s journal articles

Pubmed is an online index of biomedical articles maintained by the U.S. National Library of Medicine and the National Institutes of Health.

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