CoMEt: a statistical approach to identify combinations of mutually exclusive alterations in cancer |
| |
| Authors: | Mark DM Leiserson Hsin-Ta Wu Fabio Vandin Benjamin J. Raphael |
| |
| Affiliation: | Department of Computer Science, Brown University, 115 Waterman Street, Providence, 02912 RI USA ;Center for Computational Molecular Biology, Brown University, Providence, Box 1910, 02912 RI USA ;Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, Odense M Denmark |
| |
| Abstract: | Cancer is a heterogeneous disease with different combinations of genetic alterations driving its development in different individuals. We introduce CoMEt, an algorithm to identify combinations of alterations that exhibit a pattern of mutual exclusivity across individuals, often observed for alterations in the same pathway. CoMEt includes an exact statistical test for mutual exclusivity and techniques to perform simultaneous analysis of multiple sets of mutually exclusive and subtype-specific alterations. We demonstrate that CoMEt outperforms existing approaches on simulated and real data. We apply CoMEt to five different cancer types, identifying both known cancer genes and pathways, and novel putative cancer genes.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0700-7) contains supplementary material, which is available to authorized users. |
| |
| Keywords: | |
|
|
