CoralP
CoralP visualizes and analyzes the human phosphatome to represent protein phosphatase attributes and support interpretation of quantitative and qualitative proteomic, genomic, epidemiological, and high-throughput screening data.
Key Features:
- Phosphatome visualization: Generates visual representations of the human phosphatome focused on protein phosphatases to display family-level relationships.
- Visual encodings: Maps phosphatase attributes to edge color, node color, and node size for simultaneous quantitative and qualitative data representation.
- Multiple layouts: Supports phosphatome tree, radial network, and force-directed network layouts for alternative views of phosphatase relationships.
- Data integration: Accepts and encodes data from proteomic, genomic, epidemiological, and high-throughput screening experiments.
- Publication-quality output: Produces customizable visual representations intended for inclusion in scientific publications.
Scientific Applications:
- Phosphatase family contextualization: Situates individual protein phosphatases within the broader phosphatome to assess family relationships.
- Specificity and activity analysis: Enables exploration of phosphatase specificity and activity patterns across datasets.
- Signaling research: Facilitates analysis of phosphatase roles and interactions relevant to signaling pathways and disease mechanisms.
- Integrative dataset interpretation: Supports interpretation and comparison of proteomic, genomic, epidemiological, and high-throughput screening data mapped onto the phosphatome.
Methodology:
Implements phosphatome tree, radial network, and force-directed network visualizations and encodes attributes via edge color, node color, and node size.
Topics
Details
- License:
- MIT
- Tool Type:
- web application
- Programming Languages:
- R
- Added:
- 1/18/2021
- Last Updated:
- 2/17/2021
Operations
Publications
Min A, Deoudes E, Bond M, Davis E, Phanstiel D. CoralP: Flexible visualization of the human phosphatome. Journal of Open Source Software. 2019;4(44):1837. doi:10.21105/joss.01837. PMID:31903446. PMCID:PMC6941781.
Links
Repository
https://github.com/PhanstielLab/coralp