title: Covariance-based analyses of biological pathways.
abstract: The use of high-throughput data to study the changing behavior of biological pathways has focused mainly on examining the changes in the means of pathway genes. In this paper, we propose instead to test for changes in the co-regulated and unregulated variability of pathway genes. We assume that the eigenvalues of previously defined pathways capture biologically relevant quantities, and we develop a test for biologically meaningful changes in the eigenvalues between classes. This test reflects important and often ignored aspects of pathway behavior and provides a useful complement to traditional pathway analyses.
authors.affiliation: NanoString Technologies, 530 Fairview Ave. N, Seattle, Washington 98109, U.S.A.
authors.forename: P
authors.initials: P
authors.lastname: Danaher
authors.affiliation: Department of Statistics, University of California, One Shields Avenue, Davis, California 95616, U.S.A.
authors.forename: D
authors.initials: D
authors.lastname: Paul
authors.affiliation: Icahn Institute of Genomics and Multiscale Biology, Icahn Medical School at Mount Sinai, 1470 Madison Avenue, S8-102 New York, New York, 10029, U.S.A.
authors.forename: P
authors.initials: P
authors.lastname: Wang
keywords: gene expression; pathway analysis; spiked eigenvalue