M3C
Bioc currentMonte Carlo Reference-based Consensus Clustering
Release Lineage
Entered 3.6 · Oct 31, 2017
Current · Requires R 4.6
Description
M3C is a consensus clustering algorithm that uses a Monte Carlo simulation to eliminate overestimation of K and can reject the null hypothesis K=1.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
21 6 exported
Complexity
12 avg / 51 max
Call network
21 nodes / 17 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
3,272
Files
28
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
6
Internal functions
15
Recent export changes
Testing & CI
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.5.0
System requirements
–
C++ standard
–
License
AGPL-3
License flags
SPDX valid, OSI approved
History
Versions
18
First release
2017-10-30
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
11
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 96%
- Return-value docs
- 100%
- References docs
- 38%
Topics
Depended on by (2)
CRAN (2)
People
Christopher John