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Urgent need for consistent standards in functional enrichment analysis
Kaumadi Wijesooriya1, Sameer A Jadaan2, Kaushalya L Perera1
1Deakin University, School of Life and Environmental Sciences, Geelong, Australia.
Plos Computational Biology
|March 9, 2022
Summary
Most gene set enrichment analyses in published studies contain critical errors, such as incorrect background gene lists and lack of p-value correction. These flaws in functional enrichment analysis compromise result reliability and necessitate improved standards.
Area of Science:
- Computational biology
- Bioinformatics
- Genomics
Background:
- Gene set enrichment tests, also known as functional enrichment analysis, are widely used in computational biology.
- Concerns exist regarding the incorrect application of these methods, leading to unreliable results in peer-reviewed publications.
Purpose of the Study:
- To assess the frequency of methodological flaws in published functional enrichment analyses.
- To evaluate the impact of these flaws on study outcomes.
Main Methods:
- A systematic screen of 186 open-access research articles reporting functional enrichment results was conducted.
- Seven independent RNA-seq datasets were used to demonstrate the effect of enrichment tool misuse on results.
Main Results:
- 95% of over-representation tests lacked appropriate background gene lists or adequate description.
- 43% of analyses failed to perform p-value correction for multiple testing.
- Methodological deficiencies were not linked to journal metrics, and misuse of tools significantly altered results.
Conclusions:
- The majority of published functional enrichment studies exhibit significant methodological flaws.
- There is a critical need for establishing and enforcing stronger standards for conducting and reporting functional enrichment analyses.
