Dataset Information

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

ABSTRACT:

Background

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods.

Results

Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality.

Conclusions

Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better.

Availability

The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

SUBMITTER: De Hertogh B

PROVIDER: S-EPMC2831002 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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Publications

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

De Hertogh Benoît B De Meulder Bertrand B Berger Fabrice F Pierre Michael M Bareke Eric E Gaigneaux Anthoula A Depiereux Eric E

BMC bioinformatics 20100111

<h4>Background</h4>Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods.<h4>Results</h4>Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to dete ...[more]

PMID: 20064233

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Dataset Information

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

Background

Results

Conclusions

Availability

Publications

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

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