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Functional Genomics pp 111–136Cite as

Statistical Issues in cDNA Microarray Data Analysis

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 224))

Abstractt

Statistical considerations are frequently to the fore in the analysis of microarray data, as researchers sift through massive amounts of data and adjust for various sources of variability in order to identify the important genes among the many that are measured. This chapter summarizes some of the issues involved and provides a brief review of the analysis tools that are available to researchers to deal with these issues.

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Author information

Authors and Affiliations

  1. Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia

    Gordon K. Smyth & Terry Speed

  2. Division of Biostatistics, University of California, San Francisco, CA

    Yee Hwa Yang

  3. Department of Statistics, University of California-Berkeley, Berkeley, CA

    Terry Speed

Authors
  1. Gordon K. Smyth
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  2. Yee Hwa Yang
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  3. Terry Speed
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Editor information

Editors and Affiliations

  1. Laboratory of Genetics, NIMH/NHGRI, National Institutes of Health, Rockville, MD

    Michael J. Brownstein

  2. Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, St. Paul, MN

    Arkady B. Khodursky

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© 2003 Humana Press Inc.

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Smyth, G.K., Yang, Y.H., Speed, T. (2003). Statistical Issues in cDNA Microarray Data Analysis. In: Brownstein, M.J., Khodursky, A.B. (eds) Functional Genomics. Methods in Molecular Biology, vol 224. Humana Press. https://doi.org/10.1385/1-59259-364-X:111

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  • DOI: https://doi.org/10.1385/1-59259-364-X:111

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-291-9

  • Online ISBN: 978-1-59259-364-4

  • eBook Packages: Springer Protocols

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