Literature DB >> 15134199

Normal linear models with genetically structured residual variance heterogeneity: a case study.

Daniel Sorensen1, Rasmus Waagepetersen.   

Abstract

Normal mixed models with different levels of heterogeneity in the residual variance are fitted to pig litter size data. Exploratory analysis and model assessment is based on examination of various posterior predictive distributions. Comparisons based on Bayes factors and related criteria favour models with a genetically structured residual variance heterogeneity. There is, moreover, strong evidence of a negative correlation between the additive genetic values affecting litter size and those affecting residual variance. The models are also compared according to the purposes for which they might be used, such as prediction of 'future' data, inference about response to selection and ranking candidates for selection. A brief discussion is given of some implications for selection of the genetically structured residual variance model.

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Year:  2003        PMID: 15134199     DOI: 10.1017/s0016672303006426

Source DB:  PubMed          Journal:  Genet Res        ISSN: 0016-6723            Impact factor:   1.588


  40 in total

1.  Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes.

Authors:  Daniel Gianola; Daniel Sorensen
Journal:  Genetics       Date:  2004-07       Impact factor: 4.562

2.  Genetic Control of Environmental Variation of Two Quantitative Traits of Drosophila melanogaster Revealed by Whole-Genome Sequencing.

Authors:  Peter Sørensen; Gustavo de los Campos; Fabio Morgante; Trudy F C Mackay; Daniel Sorensen
Journal:  Genetics       Date:  2015-08-12       Impact factor: 4.562

3.  Behavioral idiosyncrasy reveals genetic control of phenotypic variability.

Authors:  Julien F Ayroles; Sean M Buchanan; Chelsea O'Leary; Kyobi Skutt-Kakaria; Jennifer K Grenier; Andrew G Clark; Daniel L Hartl; Benjamin L de Bivort
Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-07       Impact factor: 11.205

4.  Evidence for genetic control of adult weight plasticity in the snail Helix aspersa.

Authors:  Mathieu Ros; Daniel Sorensen; Rasmus Waagepetersen; Mathilde Dupont-Nivet; Magali SanCristobal; Jean-Claude Bonnet; Jacques Mallard
Journal:  Genetics       Date:  2004-12       Impact factor: 4.562

Review 5.  Developments in statistical analysis in quantitative genetics.

Authors:  Daniel Sorensen
Journal:  Genetica       Date:  2008-08-21       Impact factor: 1.082

6.  Selection for environmental variation: a statistical analysis and power calculations to detect response.

Authors:  Noelia Ibáñez-Escriche; Daniel Sorensen; Rasmus Waagepetersen; Agustín Blasco
Journal:  Genetics       Date:  2008-10-01       Impact factor: 4.562

7.  Reproducing kernel hilbert spaces regression methods for genomic assisted prediction of quantitative traits.

Authors:  Daniel Gianola; Johannes B C H M van Kaam
Journal:  Genetics       Date:  2008-04       Impact factor: 4.562

Review 8.  Drosophila bristles and the nature of quantitative genetic variation.

Authors:  Trudy F Mackay; Richard F Lyman
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-07-29       Impact factor: 6.237

9.  Linear and generalized linear models for the detection of QTL effects on within-subject variability.

Authors:  Dörte Wittenburg; Volker Guiard; Friedrich Liese; Norbert Reinsch
Journal:  Genet Res       Date:  2007-08       Impact factor: 1.588

10.  Understanding and using quantitative genetic variation.

Authors:  William G Hill
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-01-12       Impact factor: 6.237

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