Li-Xuan Qin, PhD

Attending Biostatistician

Li-Xuan Qin, PhD

Attending Biostatistician
Li-Xuan Qin

Office Phone



University of Washington

Current Research Interests

Dr. Qin develops benchmark data, analytic methods, and computational tools for enabling reproducible statistical translations of high-dimensional biomedical data. With wet-lab colleagues, she has designed and collected unique benchmark datasets to study the issue of data harmonization for microarrays and sequencing. She has built simulation algorithms and software tools to decipher the interactions between data harmonization and subsequent analysis (such as sample classification and survival prediction) and is developing statistical methods to facilitate evidence-based practice of data harmonization. Her research program in reproducible statistical learning for cancer omics data has been supported by multiple completed and ongoing grants awarded by the NIH.

Dr. Qin collaborates with multidisciplinary investigators engaged in research on soft tissue sarcoma and colorectal cancer at MSK, for design and analysis of retrospective and prospective studies. She serves as Co-Director of the Biostatistics and Bioinformatics Core of the MSK Soft Tissue Sarcoma SPORE. Over the years she has also worked with investigators studying the molecular basis of other cancer types such as breast, ovarian, pancreatic, and pediatric cancer.

Dr. Qin is a member of MSK Research Council, reviewing investigator-initiated and industry-sponsored protocols for scientific merit and priority. At the national level, she serves as Council of Sections Representative for the American Statistical Association’s Statistics in Genomics and Genetics Section and Regular Member for the NIH’s ASPA Study Section.


Selected peer-reviewed publications:

  1. Qin LX, Huang HC, Begg CB. Cautionary note on using cross-validation for molecular classification. Journal of Clinical Oncology 2016, 34:3931-3938.
  2. Ni A, Qin LX. Performance evaluation of transcriptomics data normalization for survival outcome prediction. Briefings in Bioinformatics 2021, 22:bbab257.
  3. Düren Y, Lederer J, Qin LX. Depth normalization of small RNA sequencing: using data and biology to select a suitable method. Nucleic Acids Research 2022, 50:e56.
  4. Wu Y, Yuen BW, Wei Y, Qin LX. On data normalization and batch-effect correction for tumor subtyping with microRNA data. NAR Genomics and  Bioinformatics 2023, 5:lqac100.
  5. Ni A, Liu M, Qin LX. BatMan: Mitigating batch effects via stratification for survival outcome prediction. JCO Clinical Cancer Informatics 2023, 7:e2200138.

View a full listing of Li-Xuan Qin’s journal articles.


Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.

MSK requires doctors and faculty members to report (“disclose”) the relationships and financial interests they have with external entities. As a commitment to transparency with our community, we make that information available to the public.

Li-Xuan Qin discloses the following relationships and financial interests:

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