ropls
Bioc currentPCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data
Release Lineage
Entered 3.2 · Oct 14, 2015
Current · Requires R 4.6
Description
Latent variable modeling with Principal Component Analysis (PCA) and Partial Least Squares (PLS) are powerful methods for visualization, regression, classification, and feature selection of omics data where the number of variables exceeds the number of samples and with multicollinearity among variables. Orthogonal Partial Least Squares (OPLS) enables to separately model the variation correlated (predictive) to the factor of interest and the uncorrelated (orthogonal) variation. While performing similarly to PLS, OPLS facilitates interpretation. Successful applications of these chemometrics techniques include spectroscopic data such as Raman spectroscopy, nuclear magnetic resonance (NMR), mass spectrometry (MS) in metabolomics and proteomics, but also transcriptomics data. In addition to scores, loadings and weights plots, the package provides metrics and graphics to determine the optimal number of components (e.g. with the R2 and Q2 coefficients), check the validity of the model by permutation testing, detect outliers, and perform feature selection (e.g. with Variable Importance in Projection or regression coefficients). The package can be accessed via a user interface on the Workflow4Metabolomics.org online resource for computational metabolomics (built upon the Galaxy environment).
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
25 3 exported
Complexity
17.8 avg / 162 max
Call network
25 nodes / 15 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
12,604
Files
70
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
20
Internal functions
22
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.08
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
3
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
CeCILL
License flags
not SPDX, not OSI
History
Versions
22
First release
2016-02-12
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
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
- 31%
Topics
Depended on by (13)
Bioconductor (10)
CRAN (3)
People
- Etienne A. Thevenot author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("ropls")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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