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Related Experiment Videos

Determination of the differentially expressed genes in microarray experiments using local FDR.

J Aubert1, A Bar-Hen, J J Daudin

  • 1UMR INAPG/INRA/ENGREF 518, 16, rue C, Bernard, 75231 Paris, France. aubert@inapg.fr

BMC Bioinformatics
|September 8, 2004
PubMed
Summary

Researchers developed a local False Discovery Rate (FDR) to assess individual gene significance in microarray experiments. This method provides a probability for each gene being a false positive, improving upon arbitrary thresholds.

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Area of Science:

  • Genomics
  • Statistical Bioinformatics
  • Gene Expression Analysis

Background:

  • Microarray experiments test thousands of genes for differential expression.
  • The False Discovery Rate (FDR) controls the proportion of false positives but uses an arbitrary threshold.
  • A gene-specific measure of statistical significance is needed.

Purpose of the Study:

  • To define and estimate the local False Discovery Rate (local FDR) for individual genes.
  • To provide a more precise measure of statistical significance for gene expression data.
  • To offer a valuable guideline for identifying differentially expressed genes.

Main Methods:

  • Utilized process intensity estimation methods.
  • Defined and calculated local FDR as the probability of a gene being a false positive.

Related Experiment Videos

  • Developed a global assessment rule for controlling false positive error.

    • Main Results:

    • Introduced local FDR estimates, representing the probability of a gene being a false positive.
    • Demonstrated the method's utility on three well-known datasets.
    • Provided an R routine for computing local FDR from p-values.

    Conclusions:

    • Local FDR quantifies the false positive probability for each gene.
    • Enables computation of FDR for specific gene groups or functionally related genes.
    • Offers a more nuanced approach to interpreting gene expression significance.