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SSA-ME Detection of cancer driver genes using mutual exclusivity by small subnetwork analysis

Sergio Pulido Tamayo, Bram Weytjens UGent, Dries De Maeyer and Kathleen Marchal UGent (2016) SCIENTIFIC REPORTS. 6.
abstract
Because of its clonal evolution a tumor rarely contains multiple genomic alterations in the same pathway as disrupting the pathway by one gene often is sufficient to confer the complete fitness advantage. As a result, many cancer driver genes display mutual exclusivity across tumors. However, searching for mutually exclusive gene sets requires analyzing all possible combinations of genes, leading to a problem which is typically too computationally complex to be solved without a stringent a priori filtering, restricting the mutations included in the analysis. To overcome this problem, we present SSA-ME, a network-based method to detect cancer driver genes based on independently scoring small subnetworks for mutual exclusivity using a reinforced learning approach. Because of the algorithmic efficiency, no stringent upfront filtering is required. Analysis of TCGA cancer datasets illustrates the added value of SSA-ME: well-known recurrently mutated but also rarely mutated drivers are prioritized. We show that using mutual exclusivity to detect cancer driver genes is complementary to state-of-the art approaches. This framework, in which a large number of small subnetworks are being analyzed in order to solve a computationally complex problem (SSA), can be generically applied to any problem in which local neighborhoods in a network hold useful information.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
IBCN, MUTATIONS, LUNG-CANCER, PATHWAYS, NETWORK, COMBINATIONS, EXPRESSION, SIGNATURES, DISCOVERY, PATTERNS, SERVER
journal title
SCIENTIFIC REPORTS
Sci. Rep.
volume
6
article number
36257
pages
12 pages
Web of Science type
Article
Web of Science id
000387341100001
JCR category
MULTIDISCIPLINARY SCIENCES
JCR impact factor
4.259 (2016)
JCR rank
10/64 (2016)
JCR quartile
1 (2016)
ISSN
2045-2322
DOI
10.1038/srep36257
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
A1
copyright statement
I have retained and own the full copyright for this publication
id
8173862
handle
http://hdl.handle.net/1854/LU-8173862
date created
2016-11-28 08:58:35
date last changed
2017-04-27 08:41:50
@article{8173862,
  abstract     = {Because of its clonal evolution a tumor rarely contains multiple genomic alterations in the same pathway as disrupting the pathway by one gene often is sufficient to confer the complete fitness advantage. As a result, many cancer driver genes display mutual exclusivity across tumors. However, searching for mutually exclusive gene sets requires analyzing all possible combinations of genes, leading to a problem which is typically too computationally complex to be solved without a stringent a priori filtering, restricting the mutations included in the analysis. To overcome this problem, we present SSA-ME, a network-based method to detect cancer driver genes based on independently scoring small subnetworks for mutual exclusivity using a reinforced learning approach. Because of the algorithmic efficiency, no stringent upfront filtering is required. Analysis of TCGA cancer datasets illustrates the added value of SSA-ME: well-known recurrently mutated but also rarely mutated drivers are prioritized. We show that using mutual exclusivity to detect cancer driver genes is complementary to state-of-the art approaches. This framework, in which a large number of small subnetworks are being analyzed in order to solve a computationally complex problem (SSA), can be generically applied to any problem in which local neighborhoods in a network hold useful information.},
  articleno    = {36257},
  author       = {Pulido Tamayo, Sergio and Weytjens, Bram and De Maeyer, Dries and Marchal, Kathleen},
  issn         = {2045-2322},
  journal      = {SCIENTIFIC REPORTS},
  keyword      = {IBCN,MUTATIONS,LUNG-CANCER,PATHWAYS,NETWORK,COMBINATIONS,EXPRESSION,SIGNATURES,DISCOVERY,PATTERNS,SERVER},
  language     = {eng},
  pages        = {12},
  title        = {SSA-ME Detection of cancer driver genes using mutual exclusivity by small subnetwork analysis},
  url          = {http://dx.doi.org/10.1038/srep36257},
  volume       = {6},
  year         = {2016},
}

Chicago
Pulido Tamayo, Sergio, Bram Weytjens, Dries De Maeyer, and Kathleen Marchal. 2016. “SSA-ME Detection of Cancer Driver Genes Using Mutual Exclusivity by Small Subnetwork Analysis.” Scientific Reports 6.
APA
Pulido Tamayo, S., Weytjens, B., De Maeyer, D., & Marchal, K. (2016). SSA-ME Detection of cancer driver genes using mutual exclusivity by small subnetwork analysis. SCIENTIFIC REPORTS, 6.
Vancouver
1.
Pulido Tamayo S, Weytjens B, De Maeyer D, Marchal K. SSA-ME Detection of cancer driver genes using mutual exclusivity by small subnetwork analysis. SCIENTIFIC REPORTS. 2016;6.
MLA
Pulido Tamayo, Sergio, Bram Weytjens, Dries De Maeyer, et al. “SSA-ME Detection of Cancer Driver Genes Using Mutual Exclusivity by Small Subnetwork Analysis.” SCIENTIFIC REPORTS 6 (2016): n. pag. Print.