Literature DB >> 9062080

Mixed model approaches for diallel analysis based on a bio-model.

J Zhu1, B S Weir.   

Abstract

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

Mesh:

Year:  1996        PMID: 9062080     DOI: 10.1017/s0016672300034200

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


  10 in total

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Journal:  Theor Appl Genet       Date:  2003-09-05       Impact factor: 5.699

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4.  A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES.

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6.  A penalized linear mixed model with generalized method of moments for prediction analysis on high-dimensional multi-omics data.

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7.  A general Bayesian approach to analyzing diallel crosses of inbred strains.

Authors:  Alan B Lenarcic; Karen L Svenson; Gary A Churchill; William Valdar
Journal:  Genetics       Date:  2012-02       Impact factor: 4.562

8.  Dissecting the Genetic Architecture of Shoot Growth in Carrot (Daucus carota L.) Using a Diallel Mating Design.

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9.  Bayesian Diallel Analysis Reveals Mx1-Dependent and Mx1-Independent Effects on Response to Influenza A Virus in Mice.

Authors:  Paul L Maurizio; Martin T Ferris; Gregory R Keele; Darla R Miller; Ginger D Shaw; Alan C Whitmore; Ande West; Clayton R Morrison; Kelsey E Noll; Kenneth S Plante; Adam S Cockrell; David W Threadgill; Fernando Pardo-Manuel de Villena; Ralph S Baric; Mark T Heise; William Valdar
Journal:  G3 (Bethesda)       Date:  2018-02-02       Impact factor: 3.154

10.  A Diallel of the Mouse Collaborative Cross Founders Reveals Strong Strain-Specific Maternal Effects on Litter Size.

Authors:  John R Shorter; Paul L Maurizio; Timothy A Bell; Ginger D Shaw; Darla R Miller; Terry J Gooch; Jason S Spence; Leonard McMillan; William Valdar; Fernando Pardo-Manuel de Villena
Journal:  G3 (Bethesda)       Date:  2019-05-07       Impact factor: 3.154

  10 in total

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