ComPath: an ecosystem for exploring, analyzing, and curating mappings across pathway databases

Abstract

Although pathways are widely used for the analysis and representation of biological systems, their lack of clear boundaries, their dispersion across numerous databases, and the lack of interoperability impedes the evaluation of the coverage, agreements, and discrepancies between them. Here, we present ComPath, an ecosystem that supports curation of pathway mappings between databases and fosters the exploration of pathway knowledge through several novel visualizations. We have curated mappings between three of the major pathway databases and present a case study focusing on Parkinson’s disease that illustrates how ComPath can generate new biological insights by identifying pathway modules, clusters, and cross-talks with these mappings. The ComPath source code and resources are available at https://github.com/ComPath and the web application can be accessed at https://compath.scai.fraunhofer.de/.

The Impact of Pathway Database Choice on Statistical Enrichment Analysis and Predictive Modeling

“…However, these databases tend to differ in the average number of pathways they contain, the average number of proteins per pathway, the types of biochemical interactions they incorporate, and the subcategories of pathways that they provide (e.g., signal transduction, genetic interaction, and metabolic) (Kirouac et al, 2012; Türei et al, 2016). Pathways are often also described at varying levels of detail, with diverse data types and with loosely defined boundaries (Domingo-Fernández et al, 2018). Nonetheless, most pathway analyses are still conducted exclusively by employing a single database, often chosen in part by researchers’ preferences or previous experiences (e.g., bias towards a database previously yielding good results and ease of use of a particular database) ( Table 1 ).…”

“…As a solution, we propose to integrate different pathway resources via a method where semantically analogous pathways across databases (e.g., “Notch signaling pathway” in KEGG and “Signaling by NOTCH” pathway in Reactome) are combined. This approach exploits the pathway mappings and harmonized pathway representations described in our previous work (Domingo-Fernández et al, 2018; Domingo-Fernandez et al, 2019). We demonstrate that when aided by our integrative pathway database, it is possible to better capture expected disease biology than with individual resources, and to sometimes obtain better predictions of clinical endpoints.…”

Integration of Structured Biological Data Sources using Biological Expression Language

“…Furthermore, generating high quality mappings requires a significant amount of manual effort since curators must individually investigate each pair of pathways and assess whether the pair comprises related or similar pathways occurring in the same biological context. Three Bio2BEL packages were implemented for major pathway databases (i.e., KEGG, Reactome, and WikiPathways) and extended with tools to support the first curation of mappings between their equivalent and hierarchically related pathways during the ComPath project (Domingo-Fernández et al , 2018). Each were used to store and harmonize the data underlying ComPath and its accompanying web curation interface ( https://compath.scai.fraunhofer.de ).…”

Re-curation and rational enrichment of knowledge graphs in Biological Expression Language

“…For situations when the appropriate concept/term is unclear, several tools have been developed and made freely available to the community to help curators build semantically interoperable models including the Ontology Lookup Service [OLS; (28)], the Ontology Mapping Service (OxO; https://www.ebi.ac.uk/spot/oxo), Zooma (https://www.ebi.ac.uk/spot/zooma) and CEDAR Workbench (29). Further, recent work from Domingo-Fernández et al on mapping pathways between major databases (30) and a critical assessment of their overlaps and contradictions (31) has shown that the adoption of standards like MIRIAM has been slow and that while the syntax of the varying formats used by each database may be correct, their semantic interoperability is still lacking.…”