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Related Experiment Video

Updated: Jun 22, 2026

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Error control variability in pathway-based microarray analysis.

David L Gold¹, Jeffrey C Miecznikowski, Song Liu

¹Department of Biostatistics, Roswell Park Cancer, Buffalo, NY, USA. dlgold@buffalo.edu

Bioinformatics (Oxford, England)

|June 30, 2009

Summary

This summary is machine-generated.

Researchers should control the number of false positives, not the false discovery rate (FDR), in pathway analysis. The Benjamini and Hochberg (BH) method is less robust for gene expression studies with fewer tests.

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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

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Area of Science:

Bioinformatics
Genomics
Statistical Genetics

Background:

Choosing appropriate error control procedures is crucial for identifying significant results in high-throughput gene expression studies.
Pathway analysis, involving hundreds of tests, requires careful consideration of statistical methods for error control.
Existing methods may not be optimal for the specific challenges of pathway-based analyses.

Purpose of the Study:

To compare different error control procedures for pathway analysis in gene expression studies.
To determine the most robust method for setting P-value thresholds in this context.
To provide guidance on selecting appropriate statistical approaches for researchers.

Main Methods:

Discussion and comparison of various error control procedures.
Simulations using gene expression data to evaluate method performance.
Application of methods to real-world gene expression datasets.

Main Results:

The Benjamini and Hochberg (BH) false discovery rate (FDR) method is less robust for pathway analysis due to its requirement for a large number of hypothesis tests.
Alternative error control procedures demonstrate better performance in gene expression studies with fewer tests.
Variability in test results impacts the reliability of standard FDR approaches.

Conclusions:

Researchers are advised to control the number of false positives rather than the false discovery rate (FDR) in pathway analysis.
The findings suggest that traditional FDR methods may not be the most suitable for pathway-based gene expression studies.
Alternative statistical strategies are recommended for robust error control in this field.