Literature DB >> 23101621

Revisiting global gene expression analysis.

Jakob Lovén1, David A Orlando, Alla A Sigova, Charles Y Lin, Peter B Rahl, Christopher B Burge, David L Levens, Tong Ihn Lee, Richard A Young.   

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.

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Year:  2012        PMID： 23101621      PMCID： PMC3505597          DOI： 10.1016/j.cell.2012.10.012

Source DB:  PubMed          Journal:  Cell        ISSN： 0092-8674            Impact factor:   41.582


  43 in total

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