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Brief Bioinform. 2007 Jan;8(1):22-31. Epub 2006 Aug 9.

Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity.

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  • 1Department of Statistics, The Ohio State University, 1958 Neil Avenue Columbus, Ohio 43210, USA. Hsu.1@osu.edu

Abstract

Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarray studies in various cancers have reported such gene signatures. However, the overlap of gene signatures in the same disease has been limited so far, and some reported signatures have not been reproduced in other populations. Clearly, the methods used for verifying novel gene signatures need improvement. In this article, we describe an experiment in which microarrays and sample hybridization are designed according to the statistical principles of randomization, replication and blocking. Our results show that such designs provide unbiased estimation of differential expression levels as well as powerful tests for them.

PMID:
16899493
[PubMed - indexed for MEDLINE]
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