Registration Open for Bioc2024 July 24-26


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

Bioconductor version: Release (3.19)

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 online resource for computational metabolomics (built upon the Galaxy environment).

Author: Etienne A. Thevenot [aut, cre]

Maintainer: Etienne A. Thevenot <etienne.thevenot at>

Citation (from within R, enter citation("ropls")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

ropls-vignette HTML R Script
Reference Manual PDF


biocViews Classification, ImmunoOncology, Lipidomics, MassSpectrometry, Metabolomics, PrincipalComponent, Proteomics, Regression, Software, Transcriptomics
Version 1.36.0
In Bioconductor since BioC 3.2 (R-3.2) (9 years)
License CeCILL
Depends R (>= 3.5.0)
Imports Biobase, ggplot2, graphics, grDevices, methods, plotly, stats, MultiAssayExperiment, MultiDataSet, SummarizedExperiment, utils
System Requirements
See More
Suggests BiocGenerics, BiocStyle, knitr, multtest, omicade4, rmarkdown, testthat
Linking To
Depends On Me
Imports Me ASICS, biosigner, lipidr, MultiBaC, phenomis
Suggests Me autonomics, ptairMS, structToolbox, MetabolomicsBasics
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package ropls_1.36.0.tar.gz
Windows Binary
macOS Binary (x86_64) ropls_1.36.0.tgz
macOS Binary (arm64)
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats