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Related Experiment Videos

Multidimensional local false discovery rate for microarray studies.

Alexander Ploner1, Stefano Calza, Arief Gusnanto

  • 1Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden. alexander.ploner@meb.ki.se

Bioinformatics (Oxford, England)
|December 22, 2005
PubMed
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This study introduces fdr2d, a novel method to control the false discovery rate (fdr) by accounting for gene variability in microarray analysis. The fdr2d approach improves the accuracy of identifying differentially expressed genes, especially those with low variance.

Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • The false discovery rate (fdr) is crucial for assessing differential gene expression (DE) in microarrays.
  • Controlling only the overall fdr is insufficient for genes with low variance, leading to high false positive rates.
  • A method is needed to automatically adjust for gene variability in fdr control.

Purpose of the Study:

  • To develop and present a novel fdr-controlling procedure that incorporates gene variability.
  • To generalize the local false discovery rate (fdr) to account for multiple statistics, including gene variability.
  • To improve the objective assessment of differential gene expression.

Main Methods:

  • Generalized local fdr as a function of multiple statistics (DE test statistic and standard error).

Related Experiment Videos

  • Employed a non-parametric mixture model for DE and non-DE genes.
  • Utilized permutation methods to estimate distributions for non-DE genes.
  • Developed the fdr2d approach and validated it with simulated and real microarray data.

    • Main Results:

    • The fdr2d provides an objective assessment of DE that considers gene variability.
    • fdr2d demonstrates superior performance compared to commonly used modified test statistics.
    • The method effectively addresses the issue of high false positives in genes with small variance.

    Conclusions:

    • The fdr2d method offers a more robust approach to controlling the false discovery rate in microarray studies.
    • This method enhances the reliability of identifying differentially expressed genes by accounting for variability.
    • An R-package, OCplus, is available for implementing fdr2d and other analyses.