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© Research
Publication : Bioinformatics (Oxford, England)

VarExp: estimating variance explained by genome-wide GxE summary statistics.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Bioinformatics (Oxford, England) - 01 Oct 2018

Laville V, Bentley AR, Privé F, Zhu X, Gauderman J, Winkler TW, Province M, Rao DC, Aschard H,

Link to Pubmed [PMID] – 29726908

Link to DOI – 10.1093/bioinformatics/bty379

Bioinformatics 2018 10; 34(19): 3412-3414

Many genome-wide association studies and genome-wide screening for gene-environment (GxE) interactions have been performed to elucidate the underlying mechanisms of human traits and diseases. When the analyzed outcome is quantitative, the overall contribution of identified genetic variants to the outcome is often expressed as the percentage of phenotypic variance explained. This is commonly done using individual-level genotype data but it is challenging when results are derived through meta-analyses. Here, we present R package, ‘VarExp’, that allows for the estimation of the percentage of phenotypic variance explained using summary statistics only. It allows for a range of models to be evaluated, including marginal genetic effects, GxE interaction effects and both effects jointly. Its implementation integrates all recent methodological developments and does not need external data to be uploaded by users.The R package is available at https://gitlab.pasteur.fr/statistical-genetics/VarExp.git.Supplementary data are available at Bioinformatics online.