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Revisiting Global Gene Expression Analysis
Jakob Lovén ,
David A. Orlando ,
Alla A. Sigova ,
Charles Y. Lin ,
Peter B. Rahl ,
Christopher B. Burge ,
David L. Levens ,
Tong Ihn Lee ,
Richard A. Young
October 2012
October 2012
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Abstract
Gene expression analysis is a widely used and powerful method for investigating the
transcriptional behavior of biological systems, for classifying cell states in disease,
and for many other purposes. Recent studies indicate that common assumptions currently
embedded in experimental and analytical practices can lead to misinterpretation of
global gene expression data. We discuss these assumptions and describe solutions that
should minimize erroneous interpretation of gene expression data from multiple analysis
platforms.
Copyright © 2012 Elsevier Inc. All rights reserved.