PathVisioRPC
PathVisioRPC provides programmatic access to PathVisio for creating, editing, visualizing, and statistically analyzing biological pathways from external scripting languages.
Key Features:
- Integration with scripting languages: Enables remote control of PathVisio functionality from external scripting languages via RPC.
- Pathway creation and editing: Supports creation and modification of pathway diagrams within PathVisio programmatically.
- Data visualization on pathways: Maps experimental data onto pathway elements for pathway-level visualization.
- Statistical pathway analysis: Performs statistical analyses of pathways using PathVisio's analysis capabilities invoked remotely.
- Export to image formats: Exports pathway visualizations to various image formats.
- R integration (RPathVisio): Includes the RPathVisio module to enable integration with the R environment and R-based scripts.
- Automation capabilities: Automates repetitive PathVisio tasks to enable scripted batch analyses.
- Support for pathway sources: Supports use of existing pathways from databases such as WikiPathways and custom pathways created via RPC.
Scientific Applications:
- Functional analysis of differentially expressed genes or proteins: Enables pathway-level interpretation and visualization of differentially expressed genes or proteins.
- Integration with R-based workflows and public datasets: Integrates with R data-processing scripts and packages and can be applied to NCBI GEO gene expression datasets (for example, datasets involving tumor-bearing mice treated with cyclophosphamide).
Methodology:
PathVisioRPC leverages XML-RPC to bridge PathVisio's pathway analysis capabilities with external scripting languages.
Topics
Collections
Details
- License:
- Apache-2.0
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Mac
- Programming Languages:
- R, C++, Perl, Python
- Added:
- 8/3/2017
- Last Updated:
- 7/17/2019
Operations
Publications
Bohler A, et al. Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment. BMC Bioinformatics. 2015; 16:267. doi: 10.1186/s12859-015-0708-8
PMID: 26298294