DOSE
Bioc currentDisease Ontology Semantic and Enrichment analysis
Release Lineage
Entered 2.9 · Nov 1, 2011
Current · Requires R 4.6
Description
This package implements five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring semantic similarities among DO terms and gene products. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented for discovering disease associations of high-throughput biological data.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
33 14 exported
Complexity
2.8 avg / 12 max
Call network
33 nodes / 28 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
1,932
Files
73
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
17
Internal functions
19
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.02
testthat edition
–
CI present
Yes
CI type
["github-actions"]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
25%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.5.0
System requirements
–
C++ standard
–
License
Artistic-2.0
License flags
SPDX valid, OSI approved
History
Versions
30
First release
2011-10-31
Latest release
2026-04-28
Avg cadence
189 days
Cold removal rate
100%
Dep drift
39
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 60%
- Documented parameters
- 100%
- Return-value docs
- 93%
- References docs
- 11%
Topics
Depended on by (40)
Bioconductor (37)
CRAN (3)
People
- Guangchuang Yu author maintainer
- Giovanni Dall'Olio contributor
- Vladislav Petyuk contributor
- Li-Gen Wang contributor
Cite
Cite this package
Run in R for the authors' preferred citation:
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Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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