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

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.

Documentation

Downloads