EGAGenomicsDavid Tregouethttps://ega-archive.org/dacs/EGAC00001000088EGAEGA DAC EGAC00001000088EGAdavid-alexandre.tregouet@u-bordeaux.frExpression quantitative trait loci (eQTL) mapping is a widely used tool to study the genetics of gene expression. Confounding factors and the burden of multiple testing limit the ability to map distal trans eQTLs, which is important to understand downstream genetic effects on genes and pathways. We propose a two-stage linear mixed model that first learns local directed gene-regulatory networks to then condition on the expression levels of selected genes. We show that this covariate selection approach controls for confounding factors and regulatory context, thereby increasing eQTL detection power and improving the consistency between studies. GNet-LMM is available at: https://github.com/PMBio/GNetLMM.Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression.Rakitsch Barbara B, Stegle Oliver OfalseCardiogenicsData Access Committee EGAC00001000088

2025-1-9

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