On the Utility of Pooling Biological Samples in Microarray Experiments

Over 15% of the data sets catalogued in the Gene Expression Omnibus Database involve RNA samples that have been pooled before hybridization. Pooling affects data quality and inference, but the exact effects are not yet known because pooling has not been systematically studied in the context of micro...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 102; no. 12; pp. 4252 - 4257
Main Authors Kendziorski, C., Irizarry, R. A., K.-S. Chen, Haag, J. D., Gould, M. N., Wahba, Grace
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 22.03.2005
National Acad Sciences
Subjects
Analysis of Variance
Animals
Arithmetic mean
Biological Sciences
Biostatistics
Datasets
Diet
Experiment design
Female
Gene expression
Gene Expression Profiling - methods
Gene Expression Profiling - statistics & numerical data
Genes
Nicotinic Acids - pharmacology
Oligonucleotide Array Sequence Analysis - methods
Oligonucleotide Array Sequence Analysis - statistics & numerical data
Physical Sciences
Rats
Rats, Inbred WF
Retinoid X Receptors - agonists
RNA
RNA - genetics
Statistical variance
Statistics
Tetrahydronaphthalenes - pharmacology
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Summary:Over 15% of the data sets catalogued in the Gene Expression Omnibus Database involve RNA samples that have been pooled before hybridization. Pooling affects data quality and inference, but the exact effects are not yet known because pooling has not been systematically studied in the context of microarray experiments. Here we report on the results of an experiment designed to evaluate the utility of pooling and the impact on identifying differentially expressed genes. We find that inference for most genes is not adversely affected by pooling, and we recommend that pooling be done when fewer than three arrays are used in each condition. For larger designs, pooling does not significantly improve inferences if few subjects are pooled. The realized benefits in this case do not outweigh the price paid for loss of individual specific information. Pooling is beneficial when many subjects are pooled, provided that independent samples contribute to multiple pools.
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Abbreviations: RMA, robust multiarray analysis; DE, differentially expressed; FDR, false discovery rate.
Data Deposition: The microarray data reported in this paper have been deposited in the Gene Expression Omnibus database (accession no. GSE2331).
Author contributions: C.K. and R.A.I. designed research; J.D.H., K.S.C., and M.N.G. performed research; C.K. and R.A.I. analyzed data; C.K. obtained funds to conduct the experiments; and M.N.G. is head of the laboratory that ran this experiment.
To whom correspondence should be addressed. E-mail: kendzior@biostat.wisc.edu.
Communicated by Grace Wahba, University of Wisconsin, Madison, WI, January 25, 2005
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.0500607102