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International Conference on Advances in Interdisciplinary Statistics and Combinatorics
October 12-14, 2007
University of North Carolina at Greensboro
Greensboro, North Carolina, USA

Organizers
Sat Gupta

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An Application of the new “Surrogate Variable Analysis” method to a Human Gene Expression Study
by
Youssef Idaghdour
Genetics Department, NC State University
Coauthors: John Storey, Greg Gibson

Expression heterogeneity due to genetic, environmental, demographic, and technical factors is common in gene expression studies. However, in addition to the measures variables of interest there will tend to be sources of signal due to unmeasured and/or unknown variables. Here we apply a new method, Surrogate Variable Analysis (SAV), for capturing and utilizing statistically significant sources of expression heterogeneity in a human gene expression study. Application of the new Surrogate Variable Analysis method is helping us make sense of the expression heterogeneity and increase accuracy of our genome-wide study analyses. This approach can be applied in conjunction with standard analysis techniques and will likely be an important step in gene expression analysis in the future.

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Date received: July 31, 2007


Copyright © 2007 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cavm-17.