dittoSeq
Bioc currentUser Friendly Single-Cell and Bulk RNA Sequencing Visualization
Release Lineage
Entered 3.11 · Apr 28, 2020
Current · Requires R 4.6
Description
A universal, user friendly, single-cell and bulk RNA sequencing visualization toolkit that allows highly customizable creation of color blindness friendly, publication-quality figures. dittoSeq accepts both SingleCellExperiment (SCE) and Seurat objects, as well as the import and usage, via conversion to an SCE, of SummarizedExperiment or DGEList bulk data. Visualizations include dimensionality reduction plots, heatmaps, scatterplots, percent composition or expression across groups, and more. Customizations range from size and title adjustments to automatic generation of annotations for heatmaps, overlay of trajectory analysis onto any dimensionality reduciton plot, hidden data overlay upon cursor hovering via ggplotly conversion, and many more. All with simple, discrete inputs. Color blindness friendliness is powered by legend adjustments (enlarged keys), and by allowing the use of shapes or letter-overlay in addition to the carefully selected dittoColors().
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
108 35 exported
Complexity
5.2 avg / 24 max
Call network
108 nodes / 273 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
19,679
Files
108
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
36
Internal functions
73
Testing
Has tests
Yes
Test-to-code ratio
0.83
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
6.7%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
13
First release
2020-06-04
Latest release
2026-04-28
Avg cadence
180 days
Cold removal rate
–
Dep drift
1
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 35includes a package overview page
- Examples that run
- 100%32 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 85%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| demuxlet.example | data.frame | 80 × 7 | No other package |
Topics
Depended on by (2)
Bioconductor (2)
Suggested by (4)
People
- Daniel Bunis author maintainer
- Jared Andrews author contributor
Cite
Cite this package
Run in R for the authors' entry:
citation("dittoSeq")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/bioinformatics/btaa1011.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.