ArticlePLoS computational biology2022
Nine quick tips for pathway enrichment analysis.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed.
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- Application of Systems Genetics to Investigate Molecular Pathology of Early-Onset Colorectal Cancer.Chemical biology & drug design · 2026Review
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- Omics technologies in aquafeed: unlocking the black box towards systems biology.Functional & integrative genomics · 2026Review
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- Plasma Proteomic Signatures of Physical Activity Provide Insights into Biological Impacts and its Protective Role against Dementia.Medicine and science in sports and exercise · 2026Observational
- Temporal shifts in polygenic traits track major epidemics in Western Eurasia.bioRxiv : the preprint server for biology · 2026Article
- Probing metazoan polyphosphate biology usingeLife · 2026Article
- Ten common mistakes that could ruin your enrichment analysis.PLoS computational biology · 2026Article
- Bioinformatic Analysis of microRNAs Associated with Chemotherapy-Induced Cognitive Impairment: Integration of Gene Networks and Neuroinflammatory Pathways.Biomedicines · 2026Article
- Transcriptomic Insights into Metabolic Reprogramming and Exopolysaccharide Synthesis inMarine drugs · 2026Article
- A practical guide to functional enrichment analysis.Frontiers in bioinformatics · 2026Article
- MicroRNA Enrichment and Docking-Based Evaluation of Ilomastat Targeting of MMP-2 in Esophageal Squamous Cell Carcinoma: Insights from a South African Cohort.Computational and structural biotechnology journal · 2026Article
- A Distinct Immunological Signature in Late-Onset Myasthenia Gravis: Insights from an Exploratory Proteomics Study.Annals of neurology · 2026Article
- Molecular Signatures of Early-Onset Bipolar Disorder and Schizophrenia: Transcriptomic and Machine-Learning Insights into Calcium and cAMP Signaling, Including Sex-Specific Patterns.International journal of molecular sciences · 2025Article
- Synaptic proteome diversity is shaped by the levels of glutamate receptors and their regulatory proteins.Nature communications · 2025Article
- A Critical Evaluation of Background Gene Omission in Imaging Transcriptomics.Biological psychiatry global open science · 2025Article
- The important role of standards for the uptake of transcriptomics and metabolomics based in vitro methods in regulatory toxicology.Archives of toxicology · 2025Review
- Cluefish: mining the dark matter of transcriptional data series with over-representation analysis enhanced by aggregated biological prior knowledge.NAR genomics and bioinformatics · 2025Article
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Authors and funding
2 authors.
Funding
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Abstract
Pathway enrichment analysis (PEA) is a computational biology method that identifies biological functions that are overrepresented in a group of genes more than would be expected by chance and ranks these functions by relevance. The relative abundance of genes pertinent to specific pathways is measured through statistical methods, and associated functional pathways are retrieved from online bioinformatics databases. In the last decade, along with the spread of the internet, higher availability of computational resources made PEA software tools easy to access and to use for bioinformatics practitioners worldwide. Although it became easier to use these tools, it also became easier to make mistakes that could generate inflated or misleading results, especially for beginners and inexperienced computational biologists. With this article, we propose nine quick tips to avoid common mistakes and to out a complete, sound, thorough PEA, which can produce relevant and robust results. We describe our nine guidelines in a simple way, so that they can be understood and used by anyone, including students and beginners. Some tips explain what to do before starting a PEA, others are suggestions of how to correctly generate meaningful results, and some final guidelines indicate some useful steps to properly interpret PEA results. Our nine tips can help users perform better pathway enrichment analyses and eventually contribute to a better understanding of current biology.
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