Reactome from a WikiPathways Perspective

Abstract

Reactome and WikiPathways are two of the most popular freely available databases for biological pathways. Reactome pathways are centrally curated with periodic input from selected domain experts. WikiPathways is a community-based platform where pathways are created and continually curated by any interested party. The nascent collaboration between WikiPathways and Reactome illustrates the mutual benefits of combining these two approaches. We created a format converter that converts Reactome pathways to the GPML format used in WikiPathways. In addition, we developed the ComplexViz plugin for PathVisio which simplifies looking up complex components. The plugin can also score the complexes on a pathway based on a user defined criterion. This score can then be visualized on the complex nodes using the visualization options provided by the plugin. Using the merged collection of curated and converted Reactome pathways, we demonstrate improved pathway coverage of relevant biological processes for the analysis of a previously described polycystic ovary syndrome gene expression dataset. Additionally, this conversion allows researchers to visualize their data on Reactome pathways using PathVisio's advanced data visualization functionalities. WikiPathways benefits from the dedicated focus and attention provided to the content converted from Reactome and the wealth of semantic information about interactions. Reactome in turn benefits from the continuous community curation available on WikiPathways. The research community at large benefits from the availability of a larger set of pathways for analysis in PathVisio and Cytoscape. The pathway statistics results obtained from PathVisio are significantly better when using a larger set of candidate pathways for analysis. The conversion serves as a general model for integration of multiple pathway resources developed using different approaches.

Fig 1. Mapping Reactome pathways elements to WikiPathways pathway elements.

This diagram shows the symbols used to represent different biological entities in Reactome and the corresponding symbol used to represent the same biological entity in WikiPathways.

Fig 2. A comparative view of the Abacavir transport and metabolism pathway for Homo sapiens from Reactome Database (version 54).

(a) Reactome View of Abacavir transport and metabolism (Homo sapiens) [32] and (b) Pathway view on WikiPathways(WP2712_r83598) [33].

Fig 3. Venn diagrams showing coverage of other external databases by WikiPathways and Reactome.

(a) Venn Diagram showing coverage of Gene Ontology Terms by Gene Products of WikiPathways and Reactome, (b) Venn Diagram showing coverage of Biological Process (BP), Molecular Function (MF), and Cellular Compartment (CC) Gene Ontology Terms by Gene Products of curated and reactome_approved collections of WikiPathways pathways, and (c) Venn Diagram showing coverage of the Human Metabolome Database (HMDB) by metabolites curated and reactome_approved collections of WikiPathways pathways.

Fig 4. Human granulosa cells gene expression in normal ovulatory versus PCOS women visualized on the Toll-Like Receptors Cascades pathway (WP2775_r83597) in PathVisio [44].

Human granulosa cells were isolated from ovarian aspirates of normal ovulatory and PCOS women undergoing IVF. For each sample, RNA was extracted and hybridized to an Affymetrix Gene Chip. Genes not measured appear in gray. The log fold change (logFC) is depicted with a blue to yellow color gradient corresponding to the values -2 to 2. Significant genes with a P.value < 0.05 are marked in green and the rest in red. Significant complexes with a score > 25 are marked in orange and the rest in dark gray.

Fig 5. Conversion of Reactome Java data classes to corresponding WikiPathways Java data classes.

Fig 6. A comparative view of hyperedges in a Reactome pathways and how they are converted in WikiPathways.

A hyperedge from the Abacavir transport and metabolism pathway is shown. (a) Reactome View (b) WikiPathways view, the anchors are highlighted.