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Licensed Unlicensed Requires Authentication Published by De Gruyter March 15, 2019

A multivariate linear model for investigating the association between gene-module co-expression and a continuous covariate

  • Trishanta Padayachee ORCID logo EMAIL logo , Tatsiana Khamiakova , Ziv Shkedy , Perttu Salo , Markus Perola and Tomasz Burzykowski

Abstract

A way to enhance our understanding of the development and progression of complex diseases is to investigate the influence of cellular environments on gene co-expression (i.e. gene-pair correlations). Often, changes in gene co-expression are investigated across two or more biological conditions defined by categorizing a continuous covariate. However, the selection of arbitrary cut-off points may have an influence on the results of an analysis. To address this issue, we use a general linear model (GLM) for correlated data to study the relationship between gene-module co-expression and a covariate like metabolite concentration. The GLM specifies the gene-pair correlations as a function of the continuous covariate. The use of the GLM allows for investigating different (linear and non-linear) patterns of co-expression. Furthermore, the modeling approach offers a formal framework for testing hypotheses about possible patterns of co-expression. In our paper, a simulation study is used to assess the performance of the GLM. The performance is compared with that of a previously proposed GLM that utilizes categorized covariates. The versatility of the model is illustrated by using a real-life example. We discuss the theoretical issues related to the construction of the test statistics and the computational challenges related to fitting of the proposed model.

Award Identifier / Grant number: 305280

Award Identifier / Grant number: P7/06

Funding statement: This research was funded by the MIMOmics grant of the European Union’s Seventh Framework Programme (FP7-Health-F5-2012) under the Funder Id: 10.13039/100011272, grant agreement number 305280. The support of the IAP Research Network of the Belgian state (Belgian Science Policy) Federaal Wetenschapsbeleid, Funder Id: 10.13039/501100002749, P7/06 is gratefully acknowledged.

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Supplementary Material

The online version of this article offers supplementary material (DOI: https://doi.org/10.1515/sagmb-2018-0008).


Published Online: 2019-03-15

©2019 Walter de Gruyter GmbH, Berlin/Boston

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