epivizrStandalone
epivizrStandalone provides interactive visualization of genomic data within R by integrating the 'epiviz' JavaScript application with Bioconductor genome annotations and the epivizrServer web server.
Key Features:
- Interactive visualization engine: integrates the 'epiviz' JavaScript application to render dynamic genomic visualizations.
- R-based web server: uses the epivizrServer R package to host visualization services entirely within R.
- Genome browsing with Bioconductor annotations: supports browsing arbitrary genomes using genome annotations provided by Bioconductor packages.
- Bioconductor interoperability: interoperates with the Bioconductor ecosystem of 934 interoperable packages for bioinformatic and statistical analyses.
- Quality assurance of dependencies: relies on Bioconductor packages that undergo formal initial review and continuous automated testing.
Scientific Applications:
- Exploration of high-throughput genomics data: visualize genomic tracks and regions for interpretation of sequencing-derived datasets.
- Integration with statistical workflows: combine interactive genomic visualizations with R-based statistical analyses from Bioconductor packages.
- Support for genomic and molecular biology research: enable visualization-driven interpretation for genomicists and molecular biologists.
Methodology:
Runs an epivizrServer web server within R, embeds the 'epiviz' JavaScript application for visualization, and sources genome annotations from Bioconductor packages.
Topics
Collections
Details
- License:
- MIT
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Genome visualisation
Publications
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M. Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods. 2015;12(2):115-121. doi:10.1038/nmeth.3252. PMID:25633503. PMCID:PMC4509590.