Revisiting Global Gene Expression Analysis
Name
Lovén-2012-Revisiting Global Ge.pdf
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570.69 KB
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Checksum (MD5)
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Author(s)
Loven, Jakob
Orlando, David A.
Sigova, Alla A.
Lin, Charles Y.
Rahl, Peter B.
Burge, Christopher B.
Levens, David L.
Lee, Tong Ihn
Young, Richard A.
Date Issued
October 2012
Journal
Cell
Publisher
Elsevier B.V.
Citation
Lovén, Jakob, David A. Orlando, Alla A. Sigova, Charles Y. Lin, Peter B. Rahl, Christopher B. Burge, David L. Levens, Tong Ihn Lee, and Richard A. Young. “Revisiting Global Gene Expression Analysis.” Cell 151, no. 3 (October 2012): 476–482. © 2012 Elsevier Inc.
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
Whitehead Institute for Biomedical Research
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1016/j.cell.2012.10.012
