Connectivity of variants in eQTL networks dictates reproducibility and functionality - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Preprints, Working Papers, ... Year : 2019

Connectivity of variants in eQTL networks dictates reproducibility and functionality

Abstract

Abstract Network analyses are a natural approach for identifying genetic variants and genes that work together to drive disease phenotypes. The relationship between SNPs and genes, captured in expression quantitative trait locus (eQTL) analysis, can be represented as a network with edges connecting SNPs and genes. Existing network methods treat such edges as fixed and known when they are most often thresholded estimates from eQTL regression. We consider various characterizations of an essential feature of nodes of eQTL networks, their degree centrality, that retains different data on eQTLs. We define the network metric of degree to be estimated by false discovery rates, test statistics, and p-values of the eQTL regressions in order to represent how central and potentially influential a SNP is to the network. We calculate degree metrics for data from 21 tissues from the GTEx project to assess the reproducibility, correlation across tissues, and, functional importance of degree.

Dates and versions

hal-03642299 , version 1 (15-04-2022)

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Sheila Gaynor, Maud Fagny, Xihong Lin, John Platig, John Quackenbush. Connectivity of variants in eQTL networks dictates reproducibility and functionality. 2022. ⟨hal-03642299⟩
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