Unit

UNIT 8.17 Using MEMo to Discover Mutual Exclusivity Modules in Cancer

  1. Giovanni Ciriello,
  2. Ethan Cerami,
  3. Bulent Arman Aksoy,
  4. Chris Sander,
  5. Nikolaus Schultz

Published Online: 1 MAR 2013

DOI: 10.1002/0471250953.bi0817s41

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Ciriello, G., Cerami, E., Aksoy, B. A., Sander, C. and Schultz, N. 2013. Using MEMo to Discover Mutual Exclusivity Modules in Cancer. Current Protocols in Bioinformatics. 41:8.17:8.17.1–8.17.12.

Author Information

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

Publication History

  1. Published Online: 1 MAR 2013

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. Curr. Protoc. Bioinform. 41:8.17.1-8.17.12. © 2013 by John Wiley & Sons, Inc.

Keywords:

  • mutual exclusivity;
  • network modules;
  • cancer genomics