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Linkage analysis using principal components of gene expression data

The goal of this paper is to investigate the effect of using principal components as a data reduction method for expression data in linkage analysis. We used 45 probes normalized using the Affymetrix Global Scaling that had evidence of high heritability to estimate the first 10 principal components...

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Detalles Bibliográficos
Autores principales: Atkinson, Elizabeth J, Fridley, Brooke L, Goode, Ellen L, McDonnell, Shannon K, Liu-Mares, Wen, Rabe, Kari G, Sun, Zhifu, Slager, Susan L, de Andrade, Mariza
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367556/
https://www.ncbi.nlm.nih.gov/pubmed/18466581
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author Atkinson, Elizabeth J
Fridley, Brooke L
Goode, Ellen L
McDonnell, Shannon K
Liu-Mares, Wen
Rabe, Kari G
Sun, Zhifu
Slager, Susan L
de Andrade, Mariza
author_facet Atkinson, Elizabeth J
Fridley, Brooke L
Goode, Ellen L
McDonnell, Shannon K
Liu-Mares, Wen
Rabe, Kari G
Sun, Zhifu
Slager, Susan L
de Andrade, Mariza
author_sort Atkinson, Elizabeth J
collection PubMed
description The goal of this paper is to investigate the effect of using principal components as a data reduction method for expression data in linkage analysis. We used 45 probes normalized using the Affymetrix Global Scaling that had evidence of high heritability to estimate the first 10 principal components (PC). A genome-wide linkage scan was performed on the 45 expression values and the 10 PCs using 2272 single-nucleotide polymorphisms. Our conclusions were: 1) PC analyses under-performed the single-probe analysis for known signals; 2) the PC that best reproduced the single-probe analysis was primarily composed of that probe; 3) no new signals were detected in the PC analysis; 4) no new pleiotropic effects were detected in the PC analysis.
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spelling pubmed-23675562008-05-06 Linkage analysis using principal components of gene expression data Atkinson, Elizabeth J Fridley, Brooke L Goode, Ellen L McDonnell, Shannon K Liu-Mares, Wen Rabe, Kari G Sun, Zhifu Slager, Susan L de Andrade, Mariza BMC Proc Proceedings The goal of this paper is to investigate the effect of using principal components as a data reduction method for expression data in linkage analysis. We used 45 probes normalized using the Affymetrix Global Scaling that had evidence of high heritability to estimate the first 10 principal components (PC). A genome-wide linkage scan was performed on the 45 expression values and the 10 PCs using 2272 single-nucleotide polymorphisms. Our conclusions were: 1) PC analyses under-performed the single-probe analysis for known signals; 2) the PC that best reproduced the single-probe analysis was primarily composed of that probe; 3) no new signals were detected in the PC analysis; 4) no new pleiotropic effects were detected in the PC analysis. BioMed Central 2007-12-18 /pmc/articles/PMC2367556/ /pubmed/18466581 Text en Copyright © 2007 Atkinson 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
Atkinson, Elizabeth J
Fridley, Brooke L
Goode, Ellen L
McDonnell, Shannon K
Liu-Mares, Wen
Rabe, Kari G
Sun, Zhifu
Slager, Susan L
de Andrade, Mariza
Linkage analysis using principal components of gene expression data
title Linkage analysis using principal components of gene expression data
title_full Linkage analysis using principal components of gene expression data
title_fullStr Linkage analysis using principal components of gene expression data
title_full_unstemmed Linkage analysis using principal components of gene expression data
title_short Linkage analysis using principal components of gene expression data
title_sort linkage analysis using principal components of gene expression data
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367556/
https://www.ncbi.nlm.nih.gov/pubmed/18466581
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