CytoGTA: A cytoscape plugin for identifying discriminative subnetwork markers using a game theoretic approach

S Farahmand, M H Foroughmand-Araabi, S Goliaei and Z Razaghi-Moghadam

PLOS ONE, 2017, vol. 12, issue 10, 1-12

Abstract: In recent years, analyzing genome-wide expression profiles to find genetic markers has received much attention as a challenging field of research aiming at unveiling biological mechanisms behind complex disorders. The identification of reliable and reproducible markers has lately been achieved by integrating genome-scale functional relationships and transcriptome datasets, and a number of algorithms have been developed to support this strategy. In this paper, we present a promising and easily applicable tool to accomplish this goal, namely CytoGTA, which is a Cytoscape plug-in that relies on an optimistic game theoretic approach (GTA) for identifying subnetwork markers. Given transcriptomic data of two phenotype classes and interactome data, this plug-in offers discriminative markers for the two classes. The high performance of CytoGTA would not have been achieved if the strategy of GTA was not implemented in Cytoscape. This plug-in provides a simple-to-use platform, convenient for biological researchers to interactively work with and visualize the structure of subnetwork markers. CytoGTA is one of the few available Cytoscape plug-ins for marker identification, which shows superior performance to existing methods.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0185016

DOI: 10.1371/journal.pone.0185016

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