multiClust
Bioc currentmultiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles
Release Lineage
Entered 3.3 · May 4, 2016
Current · Requires R 4.6
Description
Clustering is carried out to identify patterns in transcriptomics profiles to determine clinically relevant subgroups of patients. Feature (gene) selection is a critical and an integral part of the process. Currently, there are many feature selection and clustering methods to identify the relevant genes and perform clustering of samples. However, choosing an appropriate methodology is difficult. In addition, extensive feature selection methods have not been supported by the available packages. Hence, we developed an integrative R-package called multiClust that allows researchers to experiment with the choice of combination of methods for gene selection and clustering with ease. Using multiClust, we identified the best performing clustering methodology in the context of clinical outcome. Our observations demonstrate that simple methods such as variance-based ranking perform well on the majority of data sets, provided that the appropriate number of genes is selected. However, different gene ranking and selection methods remain relevant as no methodology works for all studies.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
9 9 exported
Complexity
12 avg / 45 max
Call network
9 nodes / 2 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
3,206
Files
37
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
9
Internal functions
0
Testing & CI
Has tests
Yes
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
0%
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
–
System requirements
–
C++ standard
–
License
GPL (>= 2)
License flags
SPDX valid, OSI approved
History
Versions
21
First release
2016-05-15
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
0
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
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
People
- Nathan Lawlor author maintainer
- Alec Fabbri author
- Joshy George author
- Peiyong Guan author
- Krish Karuturi author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("multiClust")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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