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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

Anwesha Bohler1,2, Lars M T Eijssen3, Martijn P van Iersel4

  • 1Department of Bioinformatics - BiGCaT, Maastricht University, P.O. Box 616, UNS 50 Box 19, 6200, MD, Maastricht, The Netherlands. anwesha.dutta@maastrichtuniversity.nl.

BMC Bioinformatics
|August 24, 2015
PubMed
Summary
This summary is machine-generated.

PathVisioRPC integrates biological pathway analysis directly into R and Python scripting environments, streamlining gene expression data analysis. This tool enhances pathway visualization and statistical analysis, making complex biological data more accessible for researchers.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biological pathways are crucial for interpreting gene and protein expression data.
  • Current analysis workflows often require manual integration of scripting languages and separate pathway analysis tools, leading to inefficiencies.
  • A need exists for integrated tools that allow pathway analysis within primary data analysis environments.

Purpose of the Study:

  • To develop an interface enabling direct pathway analysis from scripting languages like R and Python.
  • To enhance the capabilities of the PathVisio software by providing an accessible RPC interface.
  • To facilitate seamless integration of pathway analysis into existing bioinformatics workflows.

Main Methods:

  • Developed PathVisioRPC, an XMLRPC interface for the PathVisio software.
  • Demonstrated PathVisioRPC functionality using Python examples.
  • Integrated PathVisioRPC with R for analyzing a gene expression dataset and created RPathVisio for simplified R usage.
  • Developed an online module for ArrayAnalysis.org that utilizes PathVisioRPC.

Main Results:

  • PathVisioRPC enables pathway creation, editing, data visualization, statistical analysis, and export in multiple formats.
  • Direct integration with R packages for data processing was successfully demonstrated.
  • Online pathway analysis via ArrayAnalysis.org was enabled without software installation.
  • Automation of PathVisio tasks for repeated analysis is now possible.

Conclusions:

  • PathVisioRPC allows direct data visualization and pathway analysis within analytical environments.
  • It supports existing and newly created pathways, enhancing workflow efficiency.
  • The tool facilitates automation of visualization and analysis tasks for PathVisio users.
  • PathVisioRPC is freely available for academic and commercial use.