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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
Descripción
Sumario: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.