Our research group studies the statistical genetics of Mendelian disorders. We focus on two major application areas: methods to assess the pathogenicity of individual genomic variants, and methods to predict the clinical impact of such variants in the context of an individual's existing clinical and genetic risk factors.

These applications draw on population scale clinical and genomic data sources, and machine learning approaches. Healthy individuals often carry variants in genes that have been previously associated with disease, and there is a pressing need to distinguish between variants that will lead to disorders and those that are either incompletely penetrant or false positives.

Christopher A. Cassa
Assistant Professor of Medicine, Harvard Medical School
Geneticist, Brigham and Women's Hospital, Division of Genetics
Lecturer, Massachusetts Institute of Technology
Associate Member, Broad Institute of Harvard and MIT

Program affiliations


  • MIT Course SCM.264, a course on Databases, and Data Analytics
  • MITx Course SC4x, a course on Databases, Data Science and Machine Learning on the open access educational platform edX