Identification of consistent functional genetic modules

Miecznikowski Jeffrey C. (), Gaile Daniel P., Chen Xiwei and Tritchler David L.
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Miecznikowski Jeffrey C.: Department of Biostatistics, SUNY University at Buffalo, Buffalo NY 14214, USA
Gaile Daniel P.: Department of Biostatistics, SUNY University at Buffalo, Buffalo NY 14214, USA
Chen Xiwei: Department of Biostatistics, SUNY University at Buffalo, Buffalo NY 14214, USA
Tritchler David L.: Department of Biostatistics, SUNY University at Buffalo, Buffalo NY 14214, USA Division of Biostatistics, University of Toronto, ON M5T 3M7, Toronto, Canada

Statistical Applications in Genetics and Molecular Biology, 2016, vol. 15, issue 1, 1-18

Abstract: It is often of scientific interest to find a set of genes that may represent an independent functional module or network, such as a functional gene expression module causing a biological response, a transcription regulatory network, or a constellation of mutations jointly causing a disease. In this paper we are specifically interested in identifying modules that control a particular outcome variable such as a disease biomarker. We discuss the statistical properties that functional networks should possess and introduce the concept of network consistency which should be satisfied by real functional networks of cooperating genes, and directly use the concept in the pathway discovery method we present. Our method gives superior performance for all but the simplest functional networks.

Keywords: module; network; pathway (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1515/sagmb-2015-0026

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