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Biostatistics. 2005 Jan;6(1):111-7.

The 'miss rate' for the analysis of gene expression data.

Author information

1
Department of Statistics, Stanford University, Stanford, CA 94305, USA. jonathan.taylor@stanford.edu

Abstract

Multiple testing issues are important in gene expression studies, where typically thousands of genes are compared over two or more experimental conditions. The false discovery rate has become a popular measure in this setting. Here we discuss a complementary measure, the 'miss rate', and show how to estimate it in practice.

PMID:
15618531
DOI:
10.1093/biostatistics/kxh021
[Indexed for MEDLINE]

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