SCFA
Bioc currentSCFA: Subtyping via Consensus Factor Analysis
Release Lineage
Entered 3.12 · Oct 28, 2020
Current · Requires R 4.6
Description
Subtyping via Consensus Factor Analysis (SCFA) can efficiently remove noisy signals from consistent molecular patterns in multi-omics data. SCFA first uses an autoencoder to select only important features and then repeatedly performs factor analysis to represent the data with different numbers of factors. Using these representations, it can reliably identify cancer subtypes and accurately predict risk scores of patients.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
31 2 exported
Complexity
3.8 avg / 16 max
Call network
31 nodes / 25 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
1,199
Files
14
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
2
Internal functions
28
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
7.1%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.0
System requirements
–
C++ standard
–
License
LGPL
License flags
not SPDX, not OSI
History
Versions
12
First release
2020-10-27
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
5
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
- Duc Tran author maintainer
- Hung Nguyen author
- Tin Nguyen fnd
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("SCFA")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.
From data release v2026-08-07, which the citation names so these numbers can be found later. More on citing and the projects behind them.