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Marker‐assisted selection using ridge regression

descriptionPublicationkeyboard_double_arrow_right Article 01 Jul 1999 United Kingdom English Publisher:WileyJournal:Annals of Human Genetics, volume 63, pages 366-366 (issn: 0003-4800, eissn: 1469-1809,

Authors: Whittaker, J. C.; Thompson, R.; Denham, M. C.;

doi: 10.1111/j.1469-1809.1999.ahg634_0351_17.x , 10.1017/s0003480099377629 , 10.1017/s0016672399004462

pmid: 10816982

Marker‐assisted selection using ridge regression

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Abstract

In crosses between inbred lines, linear regression can be used to estimate the correlation of markers with a trait of interest; these marker effects then allow marker assisted selection (MAS) for quantitative traits. Usually a subset of markers to include in the model must be selected: no completely satisfactory method of doing this exists. We show that replacing this selection of markers by ridge regression can improve the mean response to selection and reduce the variability of selection response.

Country

United Kingdom

Related Organizations

University of Edinburgh
United Kingdom
Rothamsted Research
United Kingdom
University of Reading
United Kingdom
Roslin Institute
United Kingdom

Keywords

Genetic Markers, Selection, Genetic, Regression, Psychology

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	294
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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average