survClust
Bioc currentIdentification Of Clinically Relevant Genomic Subtypes Using Outcome Weighted Learning
Release Lineage
Entered 3.20 · Oct 30, 2024
Current · Requires R 4.6
Description
survClust is an outcome weighted integrative clustering algorithm used to classify multi-omic samples on their available time to event information. The resulting clusters are cross-validated to avoid over overfitting and output classification of samples that are molecularly distinct and clinically meaningful. It takes in binary (mutation) as well as continuous data (other omic types).
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
19 8 exported
Complexity
5.8 avg / 16 max
Call network
19 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
1,913
Files
43
Compiled share
4.9%
Has compiled src
Yes
Language breakdown
API
Exported functions
8
Internal functions
8
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.02
testthat edition
3
Docs
Roxygen coverage
87.5%
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
3.5.0
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
4
First release
2024-10-29
Latest release
2026-04-28
Avg cadence
181 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
- Help pages
- 12includes a package overview page
- Examples that run
- 100%12 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Repository practices
Checks run against github.com/arorarshi/survclust on 2026-10-21.
No development-tooling practices detected in the upstream repository.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| simdat | list | 1 element | No other package |
| simsurvdat | matrix | 150 × 2 | No other package |
| uvm_dat | list | 2 elements | No other package |
| uvm_survClust_cv.fit | list | 6 elements | No other package |
| uvm_survdat | matrix | 80 × 2 | No other package |
Topics
People
- Arshi Arora author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("survClust")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.