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Power of three multitrait methods for QTL detection in crossbred populations
The multitrait detections of QTL applied to a mixture of full- and half-sib families require specific strategies. Indeed, the number of parameters estimated by the multivariate methods is excessive compared with the size of the population. Thus, only multitrait methods based on a univariate analysis...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2004
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2697205/ https://www.ncbi.nlm.nih.gov/pubmed/15107270 http://dx.doi.org/10.1186/1297-9686-36-3-347 |
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author | Gilbert, Hélène Le Roy, Pascale |
author_facet | Gilbert, Hélène Le Roy, Pascale |
author_sort | Gilbert, Hélène |
collection | PubMed |
description | The multitrait detections of QTL applied to a mixture of full- and half-sib families require specific strategies. Indeed, the number of parameters estimated by the multivariate methods is excessive compared with the size of the population. Thus, only multitrait methods based on a univariate analysis of a linear combination (LC) of the traits can be extensively performed. We compared three strategies to obtain the LC of the traits. Two linear transformations were performed on the overall population. The last one was performed within each half-sib family. Their powers were compared on simulated data depending on the frequency of the two QTL alleles in each of the grand parental populations of an intercross design. The transformations from the whole population did not lead to a large loss of power even though the frequency of the QTL alleles was similar in the two grand parental populations. In these cases, applying the within-sire family transformation improved the detection when the number of progeny per sire was greater than 100. |
format | Text |
id | pubmed-2697205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26972052009-06-16 Power of three multitrait methods for QTL detection in crossbred populations Gilbert, Hélène Le Roy, Pascale Genet Sel Evol Research The multitrait detections of QTL applied to a mixture of full- and half-sib families require specific strategies. Indeed, the number of parameters estimated by the multivariate methods is excessive compared with the size of the population. Thus, only multitrait methods based on a univariate analysis of a linear combination (LC) of the traits can be extensively performed. We compared three strategies to obtain the LC of the traits. Two linear transformations were performed on the overall population. The last one was performed within each half-sib family. Their powers were compared on simulated data depending on the frequency of the two QTL alleles in each of the grand parental populations of an intercross design. The transformations from the whole population did not lead to a large loss of power even though the frequency of the QTL alleles was similar in the two grand parental populations. In these cases, applying the within-sire family transformation improved the detection when the number of progeny per sire was greater than 100. BioMed Central 2004-05-15 /pmc/articles/PMC2697205/ /pubmed/15107270 http://dx.doi.org/10.1186/1297-9686-36-3-347 Text en Copyright © 2004 INRA, EDP Sciences |
spellingShingle | Research Gilbert, Hélène Le Roy, Pascale Power of three multitrait methods for QTL detection in crossbred populations |
title | Power of three multitrait methods for QTL detection in crossbred populations |
title_full | Power of three multitrait methods for QTL detection in crossbred populations |
title_fullStr | Power of three multitrait methods for QTL detection in crossbred populations |
title_full_unstemmed | Power of three multitrait methods for QTL detection in crossbred populations |
title_short | Power of three multitrait methods for QTL detection in crossbred populations |
title_sort | power of three multitrait methods for qtl detection in crossbred populations |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2697205/ https://www.ncbi.nlm.nih.gov/pubmed/15107270 http://dx.doi.org/10.1186/1297-9686-36-3-347 |
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