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Related Experiment Videos

A note on the false discovery rate and inconsistent comparisons between experiments.

Roger Higdon1, Gerald van Belle, Eugene Kolker

  • 1Seattle Children's Research Institute, Seattle, WA 98101, USA.

Bioinformatics (Oxford, England)
|April 22, 2008
PubMed
Summary
This summary is machine-generated.

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The false discovery rate (FDR) is useful within single experiments but can lead to misinterpretations when comparing results across studies. Augment FDR with p-values, expression ratios, and variance data for robust cross-experiment analysis.

Area of Science:

  • Genomics
  • Biostatistics

Background:

  • The false discovery rate (FDR) is commonly used to manage multiple comparisons in high-throughput studies.
  • While effective for single experiments, FDR may be inappropriate for comparing results across different studies.

Purpose of the Study:

  • To demonstrate potential misinterpretations arising from using FDR to compare results across experiments.
  • To highlight the need for caution when employing FDR for cross-experimental comparisons.

Main Methods:

  • Utilized gene-expression data examples to illustrate potential pitfalls.
  • Analyzed scenarios where FDR can lead to misinterpretations in comparative analyses.

Main Results:

  • FDR-based comparisons across experiments can yield misleading conclusions.

Related Experiment Videos

  • The study identified specific examples of misinterpretation using gene-expression data.

    • Conclusions:

    • Researchers should be cautious when using FDR for comparing experimental results.
    • Augment FDR with p-values, expression ratios, standard error, variance, and raw data for meta-analyses and re-analyses, especially in high-throughput studies.