title: Mapping eQTL networks with mixed graphical Markov models.
abstract: Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular, and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this article we approach this challenge with mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene-gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes.
authors.affiliation: Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E-08003 Barcelona, Spain Research Programme on Biomedical Informatics, Institut Hospital del Mar d'Investigacions Mèdiques, E-08003 Barcelona, Spain.
authors.forename: Inma
authors.initials: I
authors.lastname: Tur
authors.affiliation: Department of Statistical Sciences, Università di Bologna, I-40126 Bologna, Italy.
authors.forename: Alberto
authors.initials: A
authors.lastname: Roverato
authors.affiliation: Department of Experimental and Health Sciences, Universitat Pompeu Fabra, E-08003 Barcelona, Spain Research Programme on Biomedical Informatics, Institut Hospital del Mar d'Investigacions Mèdiques, E-08003 Barcelona, Spain robert.castelo@upf.edu.
authors.forename: Robert
authors.identifier: http://orcid.org/0000-0003-2229-4508
authors.initials: R
authors.lastname: Castelo
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D003433:Crosses, Genetic; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D023281:Genomics / Q000379:methods; D008390:Markov Chains; D008957:Models, Genetic; D040641:Quantitative Trait Loci; D015203:Reproducibility of Results; D012984:Software; D015003:Yeasts / Q000235:genetics
keywords: conditional Gaussian distribution; eQTL; exact-likelihood-ratio test; gene network; mixed graphical Markov model