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On the utility of pooling biological samples in microarray experiments.

C Kendziorski1, R A Irizarry, K-S Chen

  • 1Department of Biostatistics and Medical Informatics and McArdle Laboratory for Cancer Research, University of Wisconsin, Madison, WI 53703, USA. kendzior@biostat.wisc.edu

Proceedings of the National Academy of Sciences of the United States of America
|March 10, 2005
PubMed
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RNA sample pooling in microarray experiments is beneficial for small sample sizes (fewer than three arrays). For larger designs, pooling offers limited advantages and risks losing individual gene expression data.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Over 15% of Gene Expression Omnibus Database datasets utilize pooled RNA samples.
  • The impact of RNA pooling on microarray data quality and differential gene expression inference remains under-investigated.

Purpose of the Study:

  • To systematically evaluate the utility of RNA pooling in microarray experiments.
  • To determine the effects of pooling on the identification of differentially expressed genes.

Main Methods:

  • A dedicated experiment was designed to assess RNA pooling strategies.
  • Analysis focused on the impact of pooling on gene expression data inference.

Main Results:

  • RNA pooling generally does not adversely affect inference for most genes.

Related Experiment Videos

  • Pooling is recommended for designs with fewer than three arrays per condition.
  • For larger designs, pooling provides minimal inferential improvement when few subjects are involved.

    • Conclusions:

    • RNA pooling can be a beneficial strategy, particularly for limited sample sizes.
    • The benefits of pooling diminish in larger experimental designs without careful consideration of subject contribution.
    • Pooling is most advantageous when many subjects contribute to multiple pools, preserving individual sample information.