Using MEMo to discover mutual exclusivity modules in cancer.
Details
Serval ID
serval:BIB_6718D2733689
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Using MEMo to discover mutual exclusivity modules in cancer.
Journal
Current protocols in bioinformatics
ISSN
1934-340X (Electronic)
ISSN-L
1934-3396
Publication state
Published
Issued date
03/2013
Peer-reviewed
Oui
Volume
8
Pages
8.17.1-8.17.12
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Publication Status: ppublish
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.
Keywords
Computational Biology/methods, Computers, DNA Copy Number Variations/genetics, Gene Regulatory Networks/genetics, Humans, Mutation/genetics, Neoplasms/genetics, Software
Pubmed
Create date
06/07/2018 12:02
Last modification date
16/04/2024 7:12