maPredictDSC
Bioc currentPhenotype prediction using microarray data: approach of the best overall team in the IMPROVER Diagnostic Signature Challenge
Release Lineage
Entered 2.13 · Oct 15, 2013
Current · Requires R 4.6
Description
This package implements the classification pipeline of the best overall team (Team221) in the IMPROVER Diagnostic Signature Challenge. Additional functionality is added to compare 27 combinations of data preprocessing, feature selection and classifier types.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
4 3 exported
Complexity
11.8 avg / 25 max
Call network
4 nodes / 1 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
884
Files
12
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
3
Internal functions
4
Testing
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
2
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
2.15.0
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
26
First release
2013-10-14
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
- Help pages
- 4 (1 internal)
- Examples that run
- 67%2 run in a plain check · 1 hold no code
- Exported functions with examples
- 100%
- Documented parameters
- 97%
- Return-value docs
- 100%
- Help pages citing references
- 75%
- maPredictDSC PDF
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Topics
People (from the free-text Author field)
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("maPredictDSC")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.