biovizBase
biovizBase provides standardized visualization utilities, color schemes, and conventions for R and the Bioconductor ecosystem to represent and interpret high-throughput genomics and molecular biology data.
Key Features:
- Interoperability: Integration with the Bioconductor ecosystem and interoperable interfaces with other Bioconductor packages; Bioconductor comprises 934 packages.
- R integration: Utilities and conventions implemented in R to support statistical analysis and visualization.
- Standardization and consistency: Provides standardized color schemes and visualization conventions for biological data visualizations.
- Quality assurance: Packages undergo formal initial review and continuous automated testing.
- Open-source distribution: Distributed as open-source within the Bioconductor project.
Scientific Applications:
- Exploratory data analysis: Visualization support for exploratory analysis of high-throughput genomics and molecular biology datasets.
- Figure generation and communication: Produces standardized graphical outputs for communicating genomic findings.
- Integration in analysis workflows: Used within Bioconductor and R workflows to combine visualization with downstream statistical analyses.
Methodology:
Implemented in R and integrated with Bioconductor, providing R-based statistical analyses combined with advanced visualization utilities, color schemes, and conventions; packages undergo formal initial review and continuous automated testing.
Topics
Collections
Details
- License:
- Artistic-2.0
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 11/25/2024
Operations
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.