Open AccessUsing MEMo to Discover Mutual Exclusivity Modules in Cancer
Author(s) -
Ciriello Giovanni,
Cerami Ethan,
Aksoy Bulent Arman,
Sander Chris,
Schultz Nikolaus
Publication year - 2013
Publication title -
current protocols in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.535
H-Index - 57
eISSN - 1934-340X
pISSN - 1934-3396
DOI - 10.1002/0471250953.bi0817s41
Subject(s) - set (abstract data type) , biology , download , computational biology , genomics , gene , process (computing) , cancer , sample (material) , computer science , genetics , world wide web , genome , programming language , chemistry , chromatography
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.