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A method dealing with a large number of correlated traits in a linkage genome scan

We propose a method to perform linkage genome scans for many correlated traits in the Genetic Analysis Workshop 15 (GAW15) data. The proposed method has two steps: first, we use a clustering method to find the tight clusters of the traits and use the first principal component (PC) of the traits in e...

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Detalles Bibliográficos
Autores principales: Feng, Tao, Zhang, Shuanglin, Sha, Qiuying
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367490/
https://www.ncbi.nlm.nih.gov/pubmed/18466587
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author Feng, Tao
Zhang, Shuanglin
Sha, Qiuying
author_facet Feng, Tao
Zhang, Shuanglin
Sha, Qiuying
author_sort Feng, Tao
collection PubMed
description We propose a method to perform linkage genome scans for many correlated traits in the Genetic Analysis Workshop 15 (GAW15) data. The proposed method has two steps: first, we use a clustering method to find the tight clusters of the traits and use the first principal component (PC) of the traits in each cluster to represent the cluster; second, we perform a linkage scan for each cluster by using the representative trait of the cluster. The results of applying the method to the GAW15 Problem 1 data indicate that most of the traits in the same cluster have the same regulators, and the representative trait measure, the first PC, can explain a large part of the total variation of all the traits in each cluster. Furthermore, considering one cluster of traits at a time may yield more linkage signals than considering traits individually.
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spelling pubmed-23674902008-05-06 A method dealing with a large number of correlated traits in a linkage genome scan Feng, Tao Zhang, Shuanglin Sha, Qiuying BMC Proc Proceedings We propose a method to perform linkage genome scans for many correlated traits in the Genetic Analysis Workshop 15 (GAW15) data. The proposed method has two steps: first, we use a clustering method to find the tight clusters of the traits and use the first principal component (PC) of the traits in each cluster to represent the cluster; second, we perform a linkage scan for each cluster by using the representative trait of the cluster. The results of applying the method to the GAW15 Problem 1 data indicate that most of the traits in the same cluster have the same regulators, and the representative trait measure, the first PC, can explain a large part of the total variation of all the traits in each cluster. Furthermore, considering one cluster of traits at a time may yield more linkage signals than considering traits individually. BioMed Central 2007-12-18 /pmc/articles/PMC2367490/ /pubmed/18466587 Text en Copyright © 2007 Feng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Feng, Tao
Zhang, Shuanglin
Sha, Qiuying
A method dealing with a large number of correlated traits in a linkage genome scan
title A method dealing with a large number of correlated traits in a linkage genome scan
title_full A method dealing with a large number of correlated traits in a linkage genome scan
title_fullStr A method dealing with a large number of correlated traits in a linkage genome scan
title_full_unstemmed A method dealing with a large number of correlated traits in a linkage genome scan
title_short A method dealing with a large number of correlated traits in a linkage genome scan
title_sort method dealing with a large number of correlated traits in a linkage genome scan
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367490/
https://www.ncbi.nlm.nih.gov/pubmed/18466587
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