American Statistical Association
The use of high-throughput biological 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 the alternative approach of testing for changes in the pattern of co-regulation of pathway genes, allowing examination of their joint behavior. We assume the eigenvalues of a-priori known pathways capture biologically relevant quantities, and we develop SETPath, a test for relevant 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.
|Date:||Wednesday, October 15, 2014|
|Time:||4:00 - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.