JSM 2005 - Toronto

Abstract #304429

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 277
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #304429
Title: Comparative Heterogeneity by Comparative Correlations
Author(s): Amanda Blackford*+ and Jeanne Kowalski and Jyoti Mehrotra and Marianna Zahurak and Saraswati Sukumar
Companies: Johns Hopkins University and Johns Hopkins University and Johns Hopkins University and Johns Hopkins University and Johns Hopkins University
Address: 550 North Broadway Ste 1103, Baltimore, MD, 21205, United States
Keywords: Filtering ; Microarray
Abstract:

We present an approach for filtering thousands of genes arrayed---some with highly complex, non linear structures---into candidate sets of individual genes characteristic of related but distinct groups. In this setting, a goal is to simultaneously compare several groups to the same reference standard to select sets of genes that exhibit common expression, among all comparative groups, apart from those genes exhibiting group specific expression. For example, in studies of diseases with histological subtypes, the genomic characterization of a condition, irrespective of its subtype, often is of interest in addition to its subtype-specific characterization. We introduce several correlation ratio statistics to examine between within-group expression heterogeneity. Similar to a general linear test approach in regression models, we examine common and specific group effects by comparing such ratio statistics based on the inclusion and exclusion of a single group relative to the remaining groups.

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Revised March 2005