Using MEMo to discover mutual exclusivity modules in cancer.

Détails

ID Serval
serval:BIB_6718D2733689
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Using MEMo to discover mutual exclusivity modules in cancer.
Périodique
Current protocols in bioinformatics
Auteur⸱e⸱s
Ciriello G., Cerami E., Aksoy B.A., Sander C., Schultz N.
ISSN
1934-340X (Electronic)
ISSN-L
1934-3396
Statut éditorial
Publié
Date de publication
03/2013
Peer-reviewed
Oui
Volume
8
Pages
8.17.1-8.17.12
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
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.
Mots-clé
Computational Biology/methods, Computers, DNA Copy Number Variations/genetics, Gene Regulatory Networks/genetics, Humans, Mutation/genetics, Neoplasms/genetics, Software
Pubmed
Création de la notice
06/07/2018 12:02
Dernière modification de la notice
16/04/2024 7:12
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