Peter Munson
Back Home Up Next

Russell D. Wolfinger
David Allison
Jenny Bryan
Lai-Har Chi
Jane Chang
Philip Dixon
Kent M. Eskridge
Deborah Glueck
David L. Gold
Susan G. Hilsenbeck
Lawrence Hunter
Rebecka Jornsten
Steen Knudsen
Laura Lazzeroni
Chen-Tuo Liao
Peter Munson
Dan Nettleton
Wei Pan
David M. Rocke
Grace S. Shieh
Lue Ping Zhao
Deepak Mav
Annette Molinaro

Significance of Gene Expression Changes Using the "Consistency" Test

Peter Munson, Mathematical and Statistical Computing Lab, National Institutes of Health

We have previously introduced the "consistency" test for determining the significance of expression changes in microarray experiments. This test shows substantially greater power than the paired t-test when the number of replicates is low. We investigated the behavior of this test its underlying assumptions have gained experience with several studies ongoing at the NIH. In most large-sample cases, results of the paired t-test and the consistency test coincide. For both tests, however, non-intuitive results can be obtained for a fraction of the tested genes. One requirement of the consistency test is that the error variance across genes is uniform. This can be easily satisfied using a suitable transformation. Two such transformations will be suggested.

Graybill Conference
June 18-20, 2003
University Park Holiday Inn
Fort Collins, CO 80526
email: Fax: (970)491-7895 Phone: (970)491-5269
Last Updated: Monday, April 07, 2003