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F1000Res. 2018 May 02;7:531. doi: 10.12688/f1000research.14776.2. eCollection 2018.

Automation of ReactomeFIViz via CyREST API.

F1000Research

Fred Loney, Guanming Wu

Affiliations

  1. Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
  2. Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.

PMID: 29946442 PMCID: PMC5998009 DOI: 10.12688/f1000research.14776.2

Abstract

Pathway- and network-based approaches project seemingly unrelated genes onto the context of pathways and networks, enhancing the analysis power that cannot be achieved via gene-based approaches. Pathway and network approaches are routinely applied in large-scale data analysis for cancer and other complicated diseases. ReactomeFIViz is a Cytoscape app, providing features for researchers to perform pathway- and network-based data analysis and visualization by leveraging manually curated Reactome pathways and highly reliable Reactome functional interaction network. To facilitate adoption of this app in bioinformatics software pipeline and workflow development, we develop a CyREST API for ReactomeFIViz by exposing some major features in the app. We describe a use case to demonstrate the use of this API in a Python-based notebook, and believe the new API will provide the community a convenient and powerful tool to perform pathway- and network-based data analysis and visualization using our app in an automatic way.

Keywords: CyREST; Cytoscape; Pathway and network; Reactome; ReactomeFIViz

Conflict of interest statement

No competing interests were disclosed.

References

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Publication Types

Grant support