Drawing SVG Graphics to Visualize and Map Genome-Wide Data on Idiograms
Overview
For whole-genome analysis, idiograms are virtually the most intuitive and effective way to map and visualize the genome-wide information. RIdeogram was developed to visualize and map whole-genome data on idiograms with no restriction of species.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 16
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 33%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- RIdeogram Usage HTML
Downloads
Dependencies
Installing RIdeogram adds 35 packages (20 with compiled code, 30 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, isoband 1.5 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.2.2Latest
- 0.2.12019-12-02 · diff ↗
- 0.2.0
- RR 3.6.0 released · 2019-04-26
- 0.1.12019-01-15 · diff ↗
- 0.1.02019-01-08
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2019-01-08
- Total releases
- 5 / 7 yrs
- License
- Artistic-2.0 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 115 KB / 13 files
- Download size
- 4.8 MB
Cite
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Run in R for the authors' preferred citation:
citation("RIdeogram")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
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