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Ciriello G, Cerami E, Aksoy BA, et al. Using MEMo to discover mutual exclusivity modules in cancer. Curr Protoc Bioinformatics. 2013;Unit 8.17doi: 10.1002/0471250953.bi0817s41.
Ciriello, G., Cerami, E., Aksoy, B. A., Sander, C., & Schultz, N. (2013). Using MEMo to discover mutual exclusivity modules in cancer. Current protocols in bioinformatics, Unit 8.17. https://doi.org/10.1002/0471250953.bi0817s41
Ciriello, Giovanni, et al. "Using MEMo to discover mutual exclusivity modules in cancer." Current protocols in bioinformatics vol. (2013): Unit 8.17. doi: https://doi.org/10.1002/0471250953.bi0817s41
Ciriello G, Cerami E, Aksoy BA, Sander C, Schultz N. Using MEMo to discover mutual exclusivity modules in cancer. Curr Protoc Bioinformatics. 2013 Mar;Unit 8.17. doi: 10.1002/0471250953.bi0817s41. PMID: 23504936; PMCID: PMC5563973.
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Curr Protoc Bioinformatics. 2013 Mar;Unit 8.17. doi: 10.1002/0471250953.bi0817s41.

Using MEMo to discover mutual exclusivity modules in cancer.

Current protocols in bioinformatics

Giovanni Ciriello, Ethan Cerami, Bulent Arman Aksoy, Chris Sander, Nikolaus Schultz

Affiliations

  1. Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.

PMID: 23504936 PMCID: PMC5563973 DOI: 10.1002/0471250953.bi0817s41

Abstract

Although individual tumors show surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co-occur in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in Cancer (MEMo). The method searches and identifies modules characterized by three properties: (1) member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. MEMo integrates multiple data types and maps genomic alterations to biological pathways. MEMo's mutual exclusivity uses a statistical model that preserves the number of alterations per gene and per sample. The MEMo software, source code and sample data sets are available for download at: http://cbio.mskcc.org/memo.

© 2013 by John Wiley & Sons, Inc.

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