title: Linkage analysis using principal components of gene expression data.
abstract: 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.
authors.affiliation: Division of Biostatistics, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 1st Street SW, Rochester, Minnesota 55905, USA. atkinson@mayo.edu
authors.forename: Elizabeth J
authors.initials: EJ
authors.lastname: Atkinson
authors.forename: Brooke L
authors.initials: BL
authors.lastname: Fridley
authors.forename: Ellen L
authors.initials: EL
authors.lastname: Goode
authors.forename: Shannon K
authors.initials: SK
authors.lastname: McDonnell
authors.forename: Wen
authors.initials: W
authors.lastname: Liu-Mares
authors.forename: Kari G
authors.initials: KG
authors.lastname: Rabe
authors.forename: Zhifu
authors.initials: Z
authors.lastname: Sun
authors.forename: Susan L
authors.initials: SL
authors.lastname: Slager
authors.forename: Mariza
authors.initials: M
authors.lastname: de Andrade