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dc.contributor.authorImprialou, Marthaen
dc.contributor.authorPetretto, Enricoen
dc.contributor.authorBottolo, Leonardoen
dc.date.accessioned2018-07-12T11:37:07Z
dc.date.available2018-07-12T11:37:07Z
dc.date.issued2017-01en
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/278055
dc.description.abstractThe aim of expression Quantitative Trait Locus (eQTL) mapping is the identification of DNA sequence variants that explain variation in gene expression. Given the recent yield of trait-associated genetic variants identified by large-scale genome-wide association analyses (GWAS), eQTL mapping has become a useful tool to understand the functional context where these variants operate and eventually narrow down functional gene targets for disease. Despite its extensive application to complex (polygenic) traits and disease, the majority of eQTL studies still rely on univariate data modeling strategies, i.e., testing for association of all transcript-marker pairs. However these "one at-a-time" strategies are (1) unable to control the number of false-positives when an intricate Linkage Disequilibrium structure is present and (2) are often underpowered to detect the full spectrum of trans-acting regulatory effects. Here we present our viewpoint on the most recent advances on eQTL mapping approaches, with a focus on Bayesian methodology. We review the advantages of the Bayesian approach over frequentist methods and provide an empirical example of polygenic eQTL mapping to illustrate the different properties of frequentist and Bayesian methods. Finally, we discuss how multivariate eQTL mapping approaches have distinctive features with respect to detection of polygenic effects, accuracy, and interpretability of the results.en
dc.format.mediumPrinten
dc.subjectModels, Statisticalen
dc.subjectBayes Theoremen
dc.subjectChromosome Mappingen
dc.subjectGene Expressionen
dc.subjectQuantitative Trait Locien
dc.subjectAlgorithmsen
dc.subjectSoftwareen
dc.subjectGenetic Variationen
dc.subjectGenome-Wide Association Studyen
dc.subjectWeb Browseren
dc.titleExpression QTLs Mapping and Analysis: A Bayesian Perspective.en
dc.typeBook chapter
prism.endingPage215
prism.publicationDate2017en
prism.startingPage189
prism.volume1488en
dc.identifier.doi10.17863/CAM.25397
rioxxterms.versionofrecord10.1007/978-1-4939-6427-7_8en
rioxxterms.versionAM*
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2017-01en
dcterms.formatPrinten
dc.contributor.orcidBottolo, Leonardo [0000-0002-6381-2327]
rioxxterms.typeBook chapteren


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