title: Tensor decomposition for multiple-tissue gene expression experiments.
abstract: Genome-wide association studies of gene expression traits and other cellular phenotypes have successfully identified links between genetic variation and biological processes. The majority of discoveries have uncovered cis-expression quantitative trait locus (eQTL) effects via mass univariate testing of SNPs against gene expression in single tissues. Here we present a Bayesian method for multiple-tissue experiments focusing on uncovering gene networks linked to genetic variation. Our method decomposes the 3D array (or tensor) of gene expression measurements into a set of latent components. We identify sparse gene networks that can then be tested for association against genetic variation across the genome. We apply our method to a data set of 845 individuals from the TwinsUK cohort with gene expression measured via RNA-seq analysis in adipose, lymphoblastoid cell lines (LCLs) and skin. We uncover several gene networks with a genetic basis and clear biological and statistical significance. Extensions of this approach will allow integration of different omics, environmental and phenotypic data sets.
authors.affiliation: Department of Statistics, University of Oxford, Oxford, UK.
authors.forename: Victoria
authors.initials: V
authors.lastname: Hore
authors.affiliation: Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
authors.forename: Ana
authors.initials: A
authors.lastname: Viñuela
authors.affiliation: Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Buil
authors.affiliation: Wellcome Trust Centre for Human Genetics, Oxford, UK.
authors.forename: Julian
authors.initials: J
authors.lastname: Knight
authors.affiliation: Wellcome Trust Centre for Human Genetics, Oxford, UK.|Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK.
authors.forename: Mark I
authors.initials: MI
authors.lastname: McCarthy
authors.affiliation: Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
authors.forename: Kerrin
authors.identifier: 0000-0003-4566-0005
authors.initials: K
authors.lastname: Small
authors.affiliation: Department of Statistics, University of Oxford, Oxford, UK.|Wellcome Trust Centre for Human Genetics, Oxford, UK.
authors.forename: Jonathan
authors.identifier: 0000-0003-0610-8322
authors.initials: J
authors.lastname: Marchini
mesh_terms: D000273:Adipose Tissue / Q000378:metabolism*; D001499:Bayes Theorem; D015331:Cohort Studies; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D005819:Genetic Markers / Q000235:genetics*; D055106:Genome-Wide Association Study; D006801:Humans; D008214:Lymphocytes / Q000378:metabolism*; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D040641:Quantitative Trait Loci; D012867:Skin / Q000378:metabolism*; D006113:United Kingdom
chemical_list: D005819:Genetic Markers