A simple method for assessing sample sizes in microarray experiments.

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Robert Tibshirani

Author Information

Robert Tibshirani: Health Research & Policy, Stanford University, Stanford, CA 94305, USA. tibs@stanford.edu

PMID: 16512900 DOI: 10.1186/1471-2105-7-106

BACKGROUND: In this short article, we discuss a simple method for assessing sample size requirements in microarray experiments.
RESULTS: Our method starts with the output from a permutation-based analysis for a set of pilot data, e.g. from the SAM package. Then for a given hypothesized mean difference and various samples sizes, we estimate the false discovery rate and false negative rate of a list of genes; these are also interpretable as per gene power and type I error. We also discuss application of our method to other kinds of response variables, for example survival outcomes.
CONCLUSION: Our method seems to be useful for sample size assessment in microarray experiments.

BMC Genomics. 2004 Nov 08;5:87 [PMID: 15533245]
Bioinformatics. 2005 Jul 1;21(13):3017-24 [PMID: 15840707]
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N01HV28183/NHLBI NIH HHS
N01-HV-28183/NHLBI NIH HHS

Computer Simulation

Models, Genetic

Oligonucleotide Array Sequence Analysis

Sample Size

Comparative Study Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

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