Journal
NATURE GENETICS
Volume 48, Issue 9, Pages 1094-+Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ng.3624
Keywords
-
Categories
Funding
- Wellcome Trust
- European Community
- NIHR Clinical Research Facility at Guy's and St Thomas' NHS Foundation Trust
- NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London
- European Union [259749]
- EPSRC through Life Sciences Interface program of the University of Oxford's Doctoral Training Center
- ERC [617306]
- MRC [MR/L01999X/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [1104931] Funding Source: researchfish
- Medical Research Council [MR/L01999X/1] Funding Source: researchfish
- European Research Council (ERC) [617306] Funding Source: European Research Council (ERC)
Ask authors/readers for more resources
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
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available