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Updated: Sep 4, 2025
11:39
A Quantitative Fitness Analysis Workflow
Published on: August 13, 2012
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A Q-Q plot aids interpretation of the false discovery rate
1Research Statistics Group, GlaxoSmithKline Medicines Research Centre, Stevenage, Hertfordshire, UK.
Biometrical Journal. Biometrische Zeitschrift
|July 15, 2022
Summary
The Benjamini-Hochberg FDR procedure can be visualized on a transformed Q-Q plot. This graphical method enhances understanding and interpretation of false discovery rates in statistical analyses.
Area of Science:
- Statistics
- Bioinformatics
- Genomics
Background:
- The Benjamini-Hochberg (BH) procedure is a standard method for controlling false discovery rates (FDR) in multiple hypothesis testing.
- Interpreting FDR values can be challenging, particularly in large-scale data analyses common in fields like genomics.
Purpose of the Study:
- To introduce a novel graphical method for visualizing the BH-FDR.
- To enhance the understanding and interpretation of BH-FDR values derived from statistical tests.
Main Methods:
- Utilized a quantile-quantile (Q-Q) plot for visualizing p-values.
- Transformed p-values to the negative-logarithmic scale.
- Represented the calculated Benjamini-Hochberg False Discovery Rates (BH-FDRs) on this transformed Q-Q plot.
Main Results:
- Demonstrated a clear method for plotting BH-FDRs on a transformed p-value Q-Q plot.
- The graphical representation facilitates direct interpretation of BH-FDRs within the context of the overall p-value distribution.
Conclusions:
- Visualizing BH-FDRs on a transformed Q-Q plot offers intuitive insights into statistical testing outcomes.
- This approach aids researchers in better understanding and interpreting false discovery rates in their specific datasets.
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