ropls

DOI: 10.18129/B9.bioc.ropls  

PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data

Bioconductor version: Release (3.16)

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>

Installation

To install this package, start R (version "4.2") 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")

 

HTML	R Script	ropls-vignette
PDF		Reference Manual
Text		NEWS

Details

biocViews	Classification, ImmunoOncology, Lipidomics, MassSpectrometry, Metabolomics, PrincipalComponent, Proteomics, Regression, Software, Transcriptomics
Version	1.30.0
In Bioconductor since	BioC 3.2 (R-3.2) (7.5 years)
License	CeCILL
Depends	R (>= 3.5.0)
Imports	Biobase, ggplot2, graphics, grDevices, methods, plotly, stats, MultiAssayExperiment, MultiDataSet, SummarizedExperiment, utils
LinkingTo
Suggests	BiocGenerics, BiocStyle, knitr, multtest, omicade4, rmarkdown, testthat
SystemRequirements
Enhances
URL	https://doi.org/10.1021/acs.jproteome.5b00354
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_1.30.0.tar.gz
Windows Binary	ropls_1.30.0.zip
macOS Binary (x86_64)	ropls_1.30.0.tgz
macOS Binary (arm64)	ropls_1.30.0.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