ropls
PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data
Bioconductor version: Release (3.17)
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).
Author: Etienne A. Thevenot [aut, cre] 
Maintainer: Etienne A. Thevenot <etienne.thevenot at cea.fr>
citation("ropls")):
Installation
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ropls")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("ropls")| ropls-vignette | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Classification, ImmunoOncology, Lipidomics, MassSpectrometry, Metabolomics, PrincipalComponent, Proteomics, Regression, Software, Transcriptomics |
| Version | 1.32.0 |
| In Bioconductor since | BioC 3.2 (R-3.2) (8 years) |
| License | CeCILL |
| Depends | R (>= 3.5.0) |
| Imports | Biobase, ggplot2, graphics, grDevices, methods, plotly, stats, MultiAssayExperiment, MultiDataSet, SummarizedExperiment, utils |
| Linking To | |
| Suggests | BiocGenerics, BiocStyle, knitr, multtest, omicade4, rmarkdown, testthat |
| System Requirements | |
| Enhances | |
| URL | https://doi.org/10.1021/acs.jproteome.5b00354 |
See More
| Depends On Me | |
| Imports Me | ASICS, biosigner, lipidr, MultiBaC, phenomis, proFIA, rqt |
| Suggests Me | autonomics, ptairMS, structToolbox |
| Links To Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | ropls_1.32.0.tar.gz |
| Windows Binary | ropls_1.32.0.zip |
| macOS Binary (x86_64) | ropls_1.32.0.tgz |
| macOS Binary (arm64) | ropls_1.31.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/ropls |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/ropls |
| Bioc Package Browser | https://code.bioconductor.org/browse/ropls/ |
| Package Short Url | https://bioconductor.org/packages/ropls/ |
| Package Downloads Report | Download Stats |