JSM 2011 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Abstract Details

Activity Number: 404
Type: Contributed
Date/Time: Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #302433
Title: Gene Identification with True Discovery Rate Degree of Association Sets and Estimates Corrected for Regression to the Mean
Author(s): Michael Richard Crager*+
Companies: Genomic Health, Inc.
Address: 301 Penobscot Drive, Redwood City, CA, 94063,
Keywords: Gene identification ; Interval hypothesis ; Regression to the mean ; Selection bias ; TDRDA set

Analyses for identifying genes with expression associated with some clinical outcome or state are often based on ranked p-values from tests of point null hypotheses of no association. Van de Wiel and Kim take the innovative approach of testing the interval null hypotheses that the degree of association for a gene is less than some value of interest against the alternative that it is greater. Combining this idea with the false discovery rate (FDR) controlling methods of Storey, Taylor and Siegmund gives a computationally simple way to identify true discovery rate degree of association (TDRDA) sets of genes among which a specified proportion are expected to have an absolute association of a specified degree or more. Genes can be ranked using the maximum lower bound (MLB) degree of association for which each gene belongs to a TDRDA set. Estimates of each gene's degree of association with approximate correction for "selection bias" due to regression to the mean (RM) are derived using simple bivariate normal theory and Efron and Tibshirani's empirical Bayes approach. TDRDA sets, the gene ranking and the RM-corrected estimates of degree of association can be displayed graphically.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2011 program

2011 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.