Estimation of quantitative genetic parameters
This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods b...
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| Published in | Philosophical transactions of the Royal Society of London. Series B. Biological sciences Vol. 360; no. 1459; pp. 1469 - 1477 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
London
The Royal Society
29.07.2005
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| Subjects | |
| Online Access | Get full text |
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| Abstract | This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill. |
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| AbstractList | This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill. This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill. This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill.This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill. This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximumlikelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill. |
| Author | Thompson, Robin Brotherstone, Sue White, Ian M.S |
| AuthorAffiliation | 1 Rothamsted Research Harpenden, Herts AL5 2JQ, UK 3 Institute of Evolutionary Biology, University of Edinburgh Ashworth Laboratories, Edinburgh EH9 3JT, UK 2 Roslin Institute (Edinburgh) Roslin, Midlothian EH25 9PS, UK |
| AuthorAffiliation_xml | – name: 2 Roslin Institute (Edinburgh) Roslin, Midlothian EH25 9PS, UK – name: 1 Rothamsted Research Harpenden, Herts AL5 2JQ, UK – name: 3 Institute of Evolutionary Biology, University of Edinburgh Ashworth Laboratories, Edinburgh EH9 3JT, UK |
| Author_xml | – sequence: 1 givenname: Robin surname: Thompson fullname: Thompson, Robin email: robin.thompson@bbsrc.ac.uk organization: Rothamsted ResearchHarpenden, Herts AL5 2JQ, UK – sequence: 2 givenname: Sue surname: Brotherstone fullname: Brotherstone, Sue organization: Institute of Evolutionary Biology, University of EdinburghAshworth Laboratories, Edinburgh EH9 3JT, UK – sequence: 3 givenname: Ian M.S surname: White fullname: White, Ian M.S organization: Institute of Evolutionary Biology, University of EdinburghAshworth Laboratories, Edinburgh EH9 3JT, UK |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/16048789$$D View this record in MEDLINE/PubMed |
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| Snippet | This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the
development of more statistically and... This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and... |
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| SubjectTerms | Analysis of Variance Animal models Animals Cattle - genetics Covariance matrices Dairying - methods Estimation methods Genetic Parameters Heritability Lactation Likelihood Functions Maximum likelihood estimation Milk Yield Models, Genetic Phenotypic traits Quantitative genetics Quantitative Trait, Heritable Residual Maximum Likelihood Statistical variance Statistics as Topic - methods Variance Components |
| Title | Estimation of quantitative genetic parameters |
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