Diallel analysis for sex-linked and maternal effects |
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Authors: | J. Zhu B. S. Weir |
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Affiliation: | (1) Agronomy Department, Zhejiang Agricultural University, 310029 Hangzhou, China;(2) Program in Statistical Genetics, Department of Statistics, North Carolina State University, 27695-8203 Raleigh, NC, USA |
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Abstract: | Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction. |
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Keywords: | Diallel analysis Sex-linked and maternal effects Variance and covariance components Genetic prediction |
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