Wittenburg_et_al-2018-Biometrical_Journal.pdf 554,89KB
1000 Titel
  • An approximate Bayesian significance test for genomic evaluations
1000 Autor/in
  1. Wittenburg, Dörte |
  2. Liebscher, Volkmar |
1000 Erscheinungsjahr 2018
1000 LeibnizOpen
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2018-08-12
1000 Erschienen in
1000 Quellenangabe
  • 2018: 1-14
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2018
1000 Lizenz
1000 Verlagsversion
  • |
1000 Ergänzendes Material
  • |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Genomic information can be used to study the genetic architecture of some trait. Not only the size of the genetic effect captured by molecular markers and their position on the genome but also the mode of inheritance, which might be additive or dominant, and the presence of interactions are interesting parameters. When searching for interacting loci, estimating the effect size and determining the significant marker pairs increases the computational burden in terms of speed and memory allocation dramatically. This study revisits a rapid Bayesian approach (fastbayes). As a novel contribution, a measure of evidence is derived to select markers with effect significantly different from zero. It is based on the credibility of the highest posterior density interval next to zero in a marginalized manner. This methodology is applied to simulated data resembling a dairy cattle population in order to verify the sensitivity of testing for a given range of type‐I error levels. A real data application complements this study. Sensitivity and specificity of fastbayes were similar to a variational Bayesian method, and a further reduction of computing time could be achieved. More than 50% of the simulated causative variants were identified. The most complex model containing different kinds of genetic effects and their pairwise interactions yielded the best outcome over a range of type‐I error levels. The validation study showed that fastbayes is a dual‐purpose tool for genomic inferences – it is applicable to predict future outcome of not‐yet phenotyped individuals with high precision as well as to estimate and test single‐marker effects. Furthermore, it allows the estimation of billions of interaction effects.
1000 Sacherschließung
lokal SNP
lokal conditional expectation
lokal epistasis
lokal genetic architecture
lokal dominance
1000 Fachgruppe
  1. Biologie |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
1000 Förderer
  1. Leibniz Institute for Farm Animal Biology (FBN) |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. Open Access Fund
1000 Dateien
  1. An approximate Bayesian significance test for genomic evaluations
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Leibniz Institute for Farm Animal Biology (FBN) |
    1000 Förderprogramm Open Access Fund
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6410417.rdf
1000 Erstellt am 2018-10-08T11:40:03.240+0200
1000 Erstellt von 122
1000 beschreibt frl:6410417
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet Mon Oct 08 11:42:00 CEST 2018
1000 Objekt bearb. Mon Oct 08 11:41:41 CEST 2018
1000 Vgl. frl:6410417
1000 Oai Id
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1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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