Literature DB >> 26412865

Covariance-based analyses of biological pathways.

P Danaher1, D Paul2, P Wang3.   

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.

Entities:  

Keywords:  gene expression; pathway analysis; spiked eigenvalue

Year:  2015        PMID: 26412865      PMCID: PMC4581526          DOI: 10.1093/biomet/asv013

Source DB:  PubMed          Journal:  Biometrika        ISSN: 0006-3444            Impact factor:   2.445


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  2 in total

1.  Homogeneity tests of covariance matrices with high-dimensional longitudinal data.

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Journal:  Biometrika       Date:  2019-05-24       Impact factor: 2.445

2.  Stepwise approach to SNP-set analysis illustrated with the Metabochip and colorectal cancer in Japanese Americans of the Multiethnic Cohort.

Authors:  John Cologne; Lenora Loo; Yurii B Shvetsov; Munechika Misumi; Philip Lin; Christopher A Haiman; Lynne R Wilkens; Loïc Le Marchand
Journal:  BMC Genomics       Date:  2018-07-09       Impact factor: 3.969

  2 in total

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