A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers

One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same molecular pathway. Several ME tests have been proposed recently, however the cu...

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Autores principales:	Rafsan Ahmed, Cesim Erten, Aissa Houdjedj, Hilal Kazan, Cansu Yalcin
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	mutual exclusivity network-centric mutual exclusivity evaluation cancer drivers cancer genomics tumor mutation load Genetics QH426-470
Acceso en línea:	https://doaj.org/article/046a0e2c37cf42c0bb9be1cbdfc8ec12
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spelling	oai:doaj.org-article:046a0e2c37cf42c0bb9be1cbdfc8ec122021-12-01T07:17:14ZA Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers1664-802110.3389/fgene.2021.746495https://doaj.org/article/046a0e2c37cf42c0bb9be1cbdfc8ec122021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.746495/fullhttps://doaj.org/toc/1664-8021One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same molecular pathway. Several ME tests have been proposed recently, however the current protocols to evaluate ME tests have two main limitations. Firstly the evaluations are mostly with respect to simulated data and secondly the evaluation metrics lack a network-centric view. The latter is especially crucial as the notion of common functionality can be achieved through searching for interaction patterns in relevant networks. We propose a network-centric framework to evaluate the pairwise significances found by statistical ME tests. It has three main components. The first component consists of metrics employed in the network-centric ME evaluations. Such metrics are designed so that network knowledge and the reference set of known cancer genes are incorporated in ME evaluations under a careful definition of proper control groups. The other two components are designed as further mechanisms to avoid confounders inherent in ME detection on top of the network-centric view. To this end, our second objective is to dissect the side effects caused by mutation load artifacts where mutations driving tumor subtypes with low mutation load might be incorrectly diagnosed as mutually exclusive. Finally, as part of the third main component, the confounding issue stemming from the use of nonspecific interaction networks generated as combinations of interactions from different tissues is resolved through the creation and use of tissue-specific networks in the proposed framework. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/NetCentric.Rafsan AhmedCesim ErtenAissa HoudjedjHilal KazanCansu YalcinFrontiers Media S.A.articlemutual exclusivitynetwork-centric mutual exclusivity evaluationcancer driverscancer genomicstumor mutation loadGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	mutual exclusivity network-centric mutual exclusivity evaluation cancer drivers cancer genomics tumor mutation load Genetics QH426-470
spellingShingle	mutual exclusivity network-centric mutual exclusivity evaluation cancer drivers cancer genomics tumor mutation load Genetics QH426-470 Rafsan Ahmed Cesim Erten Aissa Houdjedj Hilal Kazan Cansu Yalcin A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers
description	One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same molecular pathway. Several ME tests have been proposed recently, however the current protocols to evaluate ME tests have two main limitations. Firstly the evaluations are mostly with respect to simulated data and secondly the evaluation metrics lack a network-centric view. The latter is especially crucial as the notion of common functionality can be achieved through searching for interaction patterns in relevant networks. We propose a network-centric framework to evaluate the pairwise significances found by statistical ME tests. It has three main components. The first component consists of metrics employed in the network-centric ME evaluations. Such metrics are designed so that network knowledge and the reference set of known cancer genes are incorporated in ME evaluations under a careful definition of proper control groups. The other two components are designed as further mechanisms to avoid confounders inherent in ME detection on top of the network-centric view. To this end, our second objective is to dissect the side effects caused by mutation load artifacts where mutations driving tumor subtypes with low mutation load might be incorrectly diagnosed as mutually exclusive. Finally, as part of the third main component, the confounding issue stemming from the use of nonspecific interaction networks generated as combinations of interactions from different tissues is resolved through the creation and use of tissue-specific networks in the proposed framework. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/NetCentric.
format	article
author	Rafsan Ahmed Cesim Erten Aissa Houdjedj Hilal Kazan Cansu Yalcin
author_facet	Rafsan Ahmed Cesim Erten Aissa Houdjedj Hilal Kazan Cansu Yalcin
author_sort	Rafsan Ahmed
title	A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers
title_short	A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers
title_full	A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers
title_fullStr	A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers
title_full_unstemmed	A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers
title_sort	network-centric framework for the evaluation of mutual exclusivity tests on cancer drivers
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/046a0e2c37cf42c0bb9be1cbdfc8ec12
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A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers

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