Abstract #301506

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JSM 2003 Abstract #301506
Activity Number: 475
Type: Contributed
Date/Time: Thursday, August 7, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract - #301506
Title: A Method to Characterize the Association Level Between Two Experimental Conditions in Microarray Data
Author(s): Francesca Callegari*+ and Francesca Chiaromonte and David Vandenbergh and George Vogler
Companies: Bristol-Myers Squibb and Pennsylvania State University and Pennsylvania State University and Pennsylvania State University
Address: 33 Witherspoon St. Apt. 16, Princeton, NJ, 08542-3222,
Keywords: gene expressions ; experimental conditions ; data transformations ; ranks ; association ; simulated envelopes
Abstract:

In microarray studies, the expression level of thousands genes is collected across experimental conditions. We propose a way to characterize the association of expression values pertaining to any two experimental conditions. Our method deals with the case of un-replicated conditions, but can be extended to incorporate replicates when they are available. We work with various transformations of the data (e.g., ranks, weighting transforms) to render the analysis less sensitive to aberrant signals. Overall association levels are quantified through correlation measures, and tested for significance. In addition, we investigate the role of individual genes in determining the observed association. The vector of absolute gene-wise differences between the two conditions is decreasingly sorted, and plotted together with simulated "envelopes" corresponding to scenarios of positive, negative, observed and null association. The envelopes implementation employs random permutations, bootstrap, and contamination algorithms. We demonstrate our method on publicly available expression data. Our software is available at www.stat.psu.edu/~fcallegari/.

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