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Inflated false discovery rate due to volcano plots: problem and solutions.

Mitra Ebrahimpoor1, Jelle J Goeman1

  • 1Medical statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, 2333 ZA, The Netherlands.

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Summary
This summary is machine-generated.

Volcano plots can inflate false discoveries when selecting significant results. This study presents new methods for double filtering that control error rates, ensuring more reliable feature selection in data analysis.

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Area of Science:

  • Statistics
  • Bioinformatics
  • Genomics

Background:

  • Volcano plots are popular for selecting significant findings after multiple testing procedures like Benjamini-Hochberg (BH).
  • This selection method involves filtering for small adjusted P-values and large effect sizes.
  • However, BH does not guarantee error control on these filtered subsets, potentially inflating false discoveries.

Purpose of the Study:

  • To demonstrate the inflated Type I error rate associated with volcano plot selection.
  • To introduce and validate alternative double filtering methods that maintain false discovery rate control.
  • To provide a practical, accessible tool for reliable feature selection.

Main Methods:

  • Simulation experiments to quantify Type I error inflation.
  • Analysis of RNA-sequencing data to illustrate real-world impact.
  • Development and evaluation of novel double filtering procedures for multiple testing.
  • Implementation of the proposed methods in an interactive web application.

Main Results:

  • Volcano plot selection substantially inflates the Type I error rate.
  • Features with the largest estimated effect sizes are frequently false positives.
  • The proposed alternative methods effectively control the false discovery rate.
  • The interactive web application provides a user-friendly interface for the new procedures.

Conclusions:

  • Standard volcano plot selection is unreliable due to inflated false discovery rates.
  • The developed methods offer a statistically sound alternative for robust feature selection.
  • The publicly available web application facilitates the adoption of these improved techniques in research.