The driver mutations that cause cancer tend to be mutually exclusive within a given pathway across a cohort of tumors. This provides a signal we can use to identify driver mutations and pathways simultaneously from DNA sequencing data. I have developed multiple algorithms and statistical scores for identifying combinations of mutually exclusive mutations, and applied these methods in collaboration with cancer biologists.
We developed the HotNet2 algorithm to search for significantly mutated subnetworks in genome-scale protein-protein interaction networks. In this way, we can identify the pathways and protein complexes that are more mutated than expected by chance, and therefore likely to be targeted driver mutations. We applied HotNet2 to multiple projects from The Cancer Genome Atlas, including the Pan-Cancer project.
We developed the MAGI web application to reduce the computational burden for viewing mutation data on the web, especially for users who want to view private datasets with large public datasets. MAGI also includes mutation annotations, linking mutations at the protein sequence level to references in the literature. MAGI Annotations extends this functionality, allowing users to view and edit annotations for mutations and protein-protein interactions.
- A Weighted Exact Test for Mutually Exclusive Mutations in Cancer
M.D.M. Leiserson, M.A. Reyna, B.J. Raphael
In the proceedings of ECCB/Bioinformatics 2016 (to appear)
- Patterns and functional implications of rare germline variants across 12 cancer types
Nature Communications (2015)
- Comprehensive Molecular Characterization of Papillary Renal-Cell Carcinoma
New England Journal of Medicine (2015)
- CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer
M.D.M. Leiserson*, H-T. Wu*, F. Vandin, B.J. Raphael
Genome Biology (2015)
- MAGI: visualization and collaborative annotation of genomic aberrations
Nature Methods (2015)
- Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes
Nature Genetics (2015)
- Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin
- Simultaneous Identification of Multiple Driver Pathways in Cancer
M.D.M. Leiserson, D. Blokh, R. Sharan, B.J. Raphael
PLoS Computational Biology (2013)
- Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut
M.D.M. Leiserson, D. Tatar, L. Cowen, B. Hescott
Journal of Computational Biology (2011)