ArticleBMC bioinformatics2015
Comparative study on gene set and pathway topology-based enrichment methods.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.
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53 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- A practical guide to functional enrichment analysis.Frontiers in bioinformatics · 2026Article
- Red-Wine Gene Networks Linked to Exceptional Longevity in Humans.Biomolecules · 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
- Classification-based pathway analysis using GPNet with novel P-value computation.Briefings in bioinformatics · 2024Article
- Tiny Guides, Big Impact: Focus on the Opportunities and Challenges of miR-Based Treatments for ARDS.International journal of molecular sciences · 2024Review
- Benchmarking enrichment analysis methods with the disease pathway network.Briefings in bioinformatics · 2024Article
- Robustness evaluations of pathway activity inference methods on gene expression data.BMC bioinformatics · 2024Article
- bootGSEA: a bootstrap and rank aggregation pipeline for multi-study and multi-omics enrichment analyses.Frontiers in bioinformatics · 2024Article
- Article
- Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data.Briefings in bioinformatics · 2023Article
- Data-driven analysis and druggability assessment methods to accelerate the identification of novel cancer targets.Computational and structural biotechnology journal · 2023Review
- PSF toolkit: an R package for pathway curation and topology-aware analysis.Frontiers in genetics · 2023Article
- Single sample pathway analysis in metabolomics: performance evaluation and application.BMC bioinformatics · 2022Article
- CTpathway: a CrossTalk-based pathway enrichment analysis method for cancer research.Genome medicine · 2022Article
- SEMgsa: topology-based pathway enrichment analysis with structural equation models.BMC bioinformatics · 2022Article
- On the influence of several factors on pathway enrichment analysis.Briefings in bioinformatics · 2022Review
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6 authors.
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Abstract
backgroundEnrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis.
methodsWe comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods.
resultsIn the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower.
conclusionsWe conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps.
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