ArticlePloS one2018
A critical comparison of topology-based pathway analysis methods.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- A Framework for Benchmarking Pathway Reconstruction Algorithms.bioRxiv : the preprint server for biology · 2026Article
- Exploring Molecular Signature and Prognostic Biomarkers in Ovarian Cancer: Insights From Late-Stage, Recurrent, and Metastatic Tumors.Biotechnology and applied biochemistry · 2026Article
- Cell line-specific gene network enrichment analysis for interpreting continuous phenotypes.Briefings in bioinformatics · 2026Article
- A practical guide to functional enrichment analysis.Frontiers in bioinformatics · 2026Article
- Computational Approaches for Pathway-Centric Analysis of Protein Post-Translational Modifications.Proteomics · 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
- Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review.Briefings in bioinformatics · 2024Review
- Pathway analysis through mutual information.Bioinformatics (Oxford, England) · 2024Article
- Article
- A novel approach for predicting upstream regulators (PURE) that affect gene expression.Scientific reports · 2023Article
- Executable Network Models of Integrated Multiomics Data.Journal of proteome research · 2023Article
- Functional Annotation Routines Used by ABRF Bioinformatics Core Facilities - Observations, Comparisons, and Considerations.Journal of biomolecular techniques : JBT · 2023Article
- Metabolic Pathway Analysis: Advantages and Pitfalls for the Functional Interpretation of Metabolomics and Lipidomics Data.Biomolecules · 2023Article
- Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data.Briefings in bioinformatics · 2023Article
- Single sample pathway analysis in metabolomics: performance evaluation and application.BMC bioinformatics · 2022Article
- Bioinformatics roadmap for therapy selection in cancer genomics.Molecular oncology · 2022Review
- Network Pharmacology of Ginseng (Part III): Antitumor Potential of a Fixed Combination of Red Ginseng and Red Sage as Determined by Transcriptomics.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Metabolomic Profiling of End-Stage Heart Failure Secondary to Chronic Chagas Cardiomyopathy.International journal of molecular sciences · 2022Article
- Integrating knowledge and omics to decipher mechanisms via large-scale models of signaling networks.Molecular systems biology · 2022Review
- Comparing Bayesian-Based Reconstruction Strategies in Topology-Based Pathway Enrichment Analysis.Biomolecules · 2022Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
One of the aims of high-throughput gene/protein profiling experiments is the identification of biological processes altered between two or more conditions. Pathway analysis is an umbrella term for a multitude of computational approaches used for this purpose. While in the beginning pathway analysis relied on enrichment-based approaches, a newer generation of methods is now available, exploiting pathway topologies in addition to gene/protein expression levels. However, little effort has been invested in their critical assessment with respect to their performance in different experimental setups. Here, we assessed the performance of seven representative methods identifying differentially expressed pathways between two groups of interest based on gene expression data with prior knowledge of pathway topologies: SPIA, PRS, CePa, TAPPA, TopologyGSA, Clipper and DEGraph. We performed a number of controlled experiments that investigated their sensitivity to sample and pathway size, threshold-based filtering of differentially expressed genes, ability to detect target pathways, ability to exploit the topological information and the sensitivity to different pre-processing strategies. We also verified type I error rates and described the influence of overexpression of single genes, gene sets and topological motifs of various sizes on the detection of a pathway as differentially expressed. The results of our experiments demonstrate a wide variability of the tested methods. We provide a set of recommendations for an informed selection of the proper method for a given data analysis task.
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