Lin Lab
The Lin Lab, led by Dr. Xihong Lin at the Harvard T.H. Chan School of Public Health, advances genomics and human disease research using innovative statistical and machine learning methods. Our team analyzes large-scale genetic, genomic, and health data to study complex diseases, focusing on areas like whole genome sequencing, functional variant annotation, polygenic risk prediction, and gene-environment interactions. We develop scalable tools, including FAVOR and STAAR, and prioritize improving prediction accuracy for underrepresented populations.
Research Grants
The following grants and programs support the Lin Lab’s statistical methodological research:
- Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer Research (2015-2029) – the National Cancer Institute (NCI)
- Statistical Methods for Integrative Analysis of Large-Scale Multi-Ethnic Whole Genome Sequencing Studies and Biobanks of Common Diseases – the National Heart, Lung, and Blood Institute
- Impact of Genomic Variation on Function (IGVF) – Program of the National Human Genome Research Institute (NHGRI)
- Integrative Analysis of Lung Cancer Etiology and Risk – Baylor College of Medicine
- T32 training grant on interdisciplinary training in statistical genetics and computational biology
- Emerging Statistical and Quantitative Issues in Genomic Research in Health Sciences – National Science Foundation
- Interactive Data Portals and Robust Analytics Tools to Wrap PASC Cohorts (iDRAW) – Massachusetts General Hospital
- Predictive Modeling of the Functional and Phenotypic Impacts of Genetic Variants – University of Massachusetts Medical School