Differential Expression

Huber, W.; Scholtens, D.; Hahne, F.; von Heydebreck, A.

doi:10.1007/978-0-387-77240-0_7

W. Huber⁸,
D. Scholtens⁹,
F. Hahne¹⁰ &
…
A. von Heydebreck¹¹

Part of the book series: Use R! ((USE R))

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Abstract

In this chapter we will cover some of the basic principles of finding differentially expressed genes. We cover nonspecific filtering, multiple testing, the moderated test statistics provided by the limma package, and gene selection by ROC curves.

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Authors and Affiliations

Wellcome Trust Genome Campus, European Bioinformatics Institute, EMBL Outstation Hinxton, Hinxton, Cambridge, CB10 1SD, UK
W. Huber
Department of Preventive Medicine, Northwestern University, Chicago, IL, USA
D. Scholtens
Division of Public Health Sciences, Program in Computational Biology, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue, N., M2-B876, PO Box 19024, Seattle, WA, 98109-1024, USA
F. Hahne
Global Technologies, Merck KGaA, Darmstadt, FRG, Seattle, WA, USA
A. von Heydebreck

Authors

W. Huber
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D. Scholtens
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F. Hahne
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A. von Heydebreck
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Correspondence to W. Huber .

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Huber, W., Scholtens, D., Hahne, F., von Heydebreck, A. (2008). Differential Expression. In: Bioconductor Case Studies. Use R!. Springer, New York, NY. https://doi.org/10.1007/978-0-387-77240-0_7

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DOI: https://doi.org/10.1007/978-0-387-77240-0_7
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-77239-4
Online ISBN: 978-0-387-77240-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)

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