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How to deal with genotype uncertainty in variance component quantitative trait loci analyses
Högskolan Dalarna, Akademin Industri och samhälle, Statistik.ORCID-id: 0000-0003-4390-1979
Högskolan Dalarna, Akademin Industri och samhälle, Statistik.ORCID-id: 0000-0002-1057-5401
2011 (engelsk)Inngår i: Genetics Research, ISSN 0016-6723, Vol. 93, nr 5, s. 333-342Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

sted, utgiver, år, opplag, sider
Cambridge University Press , 2011. Vol. 93, nr 5, s. 333-342
HSV kategori
Forskningsprogram
Komplexa system - mikrodataanalys, Statistisk modellering är grunden till en ökad förståelse inom genetik!
Identifikatorer
URN: urn:nbn:se:du-6090DOI: 10.1017/S0016672311000152ISI: 000295808300002OAI: oai:dalea.du.se:6090DiVA, id: diva2:520497
Tilgjengelig fra: 2011-11-24 Laget: 2011-11-24 Sist oppdatert: 2015-06-16bibliografisk kontrollert

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