CoMEt: a statistical approach to identify combinations of mutually exclusive alterations in cancer
Year: 2015
Type: article
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.
Source: Genome biology
Institutions: Brown University, University of Southern Denmark
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,490
Awards: Analytical Approaches to Massive Data Computation with Applications to Genomics, Computational Characterization of Genetic Heterogeneity, CAREER: Algorithms for Next-Generation Genomics, Computational Approaches for Structural Variation Studies in Genomes, G6671297155, III: Small: Algorithmic Approaches for Pathway and Gene Group Analysis in Genetic Studies, Graduate Research Fellowships
OpenAlex ID: W1911343030