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. 2024 Jun 3;40(6):btae338.
doi: 10.1093/bioinformatics/btae338.

ReactomeGSA: new features to simplify public data reuse

Affiliations

ReactomeGSA: new features to simplify public data reuse

Alexander Grentner et al. Bioinformatics. .

Abstract

Motivation: ReactomeGSA is part of the Reactome knowledgebase and one of the leading multi-omics pathway analysis platforms. ReactomeGSA provides access to quantitative pathway analysis methods supporting different 'omics data types. Additionally, ReactomeGSA can process different datasets simultaneously, leading to a comparative pathway analysis that can also be performed across different species.

Results: We present a major update to the ReactomeGSA analysis platforms that greatly simplifies the reuse and direct integration of public data. In order to increase the number of available datasets, we developed the new grein_loader Python application that can directly fetch experiments from the GREIN resource. This enabled us to support both EMBL-EBI's Expression Atlas and GEO RNA-seq Experiments Interactive Navigator within ReactomeGSA. To further increase the visibility and simplify the reuse of public datasets, we integrated a novel search function into ReactomeGSA that enables users to search for public datasets across both supported resources. Finally, we completely re-developed ReactomeGSA's web-frontend and R/Bioconductor package to support the new search and loading features, and greatly simplify the use of ReactomeGSA.

Availability and implementation: The new ReactomeGSA web frontend is available at https://www.reactome.org/gsa with an built-in, interactive tutorial. The ReactomeGSA R package (https://bioconductor.org/packages/release/bioc/html/ReactomeGSA.html) is available through Bioconductor and shipped with detailed documentation and vignettes. The grein_loader Python application is available through the Python Package Index (pypi). The complete source code for all applications is available on GitHub at https://github.com/grisslab/grein_loader and https://github.com/reactome.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
Schematic workflow of the public data integration and updated features in ReactomeGSA. Data can be directly loaded from GREIN, through the newly developed grein_loader Python package, and EMBL-EBI’s Expression Atlas. ReactomeGSA’s web interface was completely re-developed and now contains an integrated search function for all public datasets, an interactive tutorial, and improved functions to annotate large datasets. Finally, our R/Bioconductor package was updated to support the search and direct download of public datasets from all supported external resources.

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