Literature DB >> 1918547

Derivation, calculation, and use of national animal model information.

P M VanRaden1, G R Wiggans.   

Abstract

New terms and definitions were developed to explain national USDA genetic evaluations computed by an animal model. An animal's PTA combines information from its own records and records of all its relatives through a weighted average of 1) average of parents' evaluations, 2) half of its yield deviation, and 3) average across progeny of twice progeny evaluation minus mate's evaluation. Yield deviation is a weighted average of a cow's lactation yields minus solutions for management group, herd-sire, and permanent environmental effects. Bulls do not have yield deviations; however, a weighted adjusted for mates' merit can provide a useful, unregressed measure of daughter performance. Reliability is the squared correlation of predicted and true transmitting ability. An animal's parents, own records, and progeny each contribute amounts of information measured in daughter equivalents. Reliability of USDA evaluations then is computed as (total daughter equivalents)/(total daughter equivalents + 14).

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Year:  1991        PMID: 1918547     DOI: 10.3168/jds.S0022-0302(91)78453-1

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  73 in total

1.  Simultaneous mining of linkage and linkage disequilibrium to fine map quantitative trait loci in outbred half-sib pedigrees: revisiting the location of a quantitative trait locus with major effect on milk production on bovine chromosome 14.

Authors:  Frédéric Farnir; Bernard Grisart; Wouter Coppieters; Juliette Riquet; Paulette Berzi; Nadine Cambisano; Latifa Karim; Myriam Mni; Sirja Moisio; Patricia Simon; Danny Wagenaar; Johanna Vilkki; Michel Georges
Journal:  Genetics       Date:  2002-05       Impact factor: 4.562

2.  Multitrait fine mapping of quantitative trait loci using combined linkage disequilibria and linkage analysis.

Authors:  M S Lund; P Sørensen; B Guldbrandtsen; D A Sorensen
Journal:  Genetics       Date:  2003-01       Impact factor: 4.562

3.  Estimation of quantitative trait locus allele frequency via a modified granddaughter design.

Authors:  Joel Ira Weller; Hayim Weller; David Kliger; Micha Ron
Journal:  Genetics       Date:  2002-10       Impact factor: 4.562

4.  A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. II. A simulation study.

Authors:  G Thaller; I Hoeschele
Journal:  Theor Appl Genet       Date:  1996-11       Impact factor: 5.699

5.  Bayesian analysis of linkage between genetic markers and quantitative trait loci. II. Combining prior knowledge with experimental evidence.

Authors:  I Hoeschele; P M Vanraden
Journal:  Theor Appl Genet       Date:  1993-02       Impact factor: 5.699

6.  A hidden markov model combining linkage and linkage disequilibrium information for haplotype reconstruction and quantitative trait locus fine mapping.

Authors:  Tom Druet; Michel Georges
Journal:  Genetics       Date:  2009-12-14       Impact factor: 4.562

7.  A new approach to the problem of multiple comparisons in the genetic dissection of complex traits.

Authors:  J I Weller; J Z Song; D W Heyen; H A Lewin; M Ron
Journal:  Genetics       Date:  1998-12       Impact factor: 4.562

8.  Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree.

Authors:  Q Zhang; D Boichard; I Hoeschele; C Ernst; A Eggen; B Murkve; M Pfister-Genskow; L A Witte; F E Grignola; P Uimari; G Thaller; M D Bishop
Journal:  Genetics       Date:  1998-08       Impact factor: 4.562

9.  A rank-based nonparametric method for mapping quantitative trait loci in outbred half-sib pedigrees: application to milk production in a granddaughter design.

Authors:  W Coppieters; A Kvasz; F Farnir; J J Arranz; B Grisart; M Mackinnon; M Georges
Journal:  Genetics       Date:  1998-07       Impact factor: 4.562

10.  Genetic variants related to gap junctions and hormone secretion influence conception rates in cows.

Authors:  Mayumi Sugimoto; Shinji Sasaki; Yusaku Gotoh; Yuuki Nakamura; Yoshito Aoyagi; Takayoshi Kawahara; Yoshikazu Sugimoto
Journal:  Proc Natl Acad Sci U S A       Date:  2013-11-11       Impact factor: 11.205

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