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Bioinformatics Advance Access published online on November 16, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn591
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Power enhancement via multivariate outlier testing with gene expression arrays

Adam Asare 1,*, Zhong Gao 1,*, Vincent J. Carey 2, Richard Wang 1 and Vicki Seyfert-Margolis 1,{dagger}

1Immune Tolerance Network, University of California - San Francisco, San Francisco, CA 94143
2Channing Laboratory, Brigham and Woman's Hospital, Harvard Medical School, Boston, MA 02115

{dagger}To whom correspondence should be addressed. Vicki Seyfert-Margolis, E-mail: vseyfert{at}immunetolerance.org


  Abstract

Motivation: As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing.

Results: We applied our approach to several data resources. First, as a negative control, we found that the Affymetrix and Illumina contributions to MAQC data were free from outliers at a nominal outlier flagging rate of {alpha} = 0:01. Second, we created a tunable framework for artificially corrupting intensity data from the Affymetrix Latin Square spikein experiment to allow investigation of sensitivity and specificity of QA criteria. Third, we applied the procedure to 507 Affymetrix microarray GeneChips processed with RNA from human peripheral blood samples. We show that exclusion of arrays by this approach substantially increases inferential power, or the ability to detect differential expression, in large clinical studies.

Availability: Subversion checkout at https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/arrayMvout, https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/affyContam (credentials: readonly/readonly),

Contact: aasare{at}immunetolerance.org

Associate Editor: Dr. Trey Ideker

*Authors contributed equally

Received on May 13, 2008; revised on October 10, 2008; accepted on November 11, 2008

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