netgwas: An R Package for Network-Based GenomeWide Association Studies

Pariya Behrouzi*, Danny Arends, Ernst C. Wit

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
12 Downloads (Pure)

Abstract

Graphical models are a powerful tool in modelling and analysing complex biological associations in high-dimensional data. The R-package netgwas implements the recent methodological development on copula graphical models to (i) construct linkage maps, (ii) infer linkage disequilibrium networks from genotype data, and (iii) detect high-dimensional genotype-phenotype networks. The netgwas learns the structure of networks from ordinal data and mixed ordinal-and-continuous data. Here, we apply the functionality in netgwas to various multivariate example datasets taken from the literature to demonstrate the kind of insight that can be obtained from the package. We show that our package offers a more realistic association analysis than the classical approaches, as it discriminates between direct and induced correlations by adjusting for the effect of all other variables while performing pairwise associations. This feature controls for spurious interactions between variables that can arise from conventional approaches in a biological sense.

Original languageEnglish
Pages (from-to)18-37
Number of pages20
JournalR Journal
Volume14
Issue number4
Early online date4 Dec 2022
DOIs
Publication statusPublished - 10 Feb 2023
Externally publishedYes

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