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 <firstname.lastname@example.org>|
|Date of publication||None|
|Maintainer||Etienne A. Thevenot <email@example.com>|
aminoacids: Amino-Acids Dataset
cellulose: NIR-Viscosity example data set to illustrate multivariate...
checkW4M: Checking the consistency of an ExpressionSet instance with...
coef: Coefficients method for (O)PLS models
cornell: Octane of various blends of gasoline
fitted: Fitted method for 'opls' objects
foods: Food consumption patterns accross European countries (FOODS)
getLoadingMN: getLoadingMN method for PCA/(O)PLS(-DA) models
getPcaVarVn: getPcaVarVn method for PCA models
getScoreMN: getScoreMN method for PCA/(O)PLS(-DA) models
getSubsetVi: getSubsetVi method for (O)PLS(-DA) models
getSummaryDF: getSummaryDF method for PCA/(O)PLS models
getVipVn: getVipVn method for (O)PLS(-DA) models
getWeightMN: getWeightMN method for (O)PLS(-DA) models
linnerud: Linnerud Dataset
lowarp: A multi response optimization data set (LOWARP)
mark: 'mark' Dataset
opls: PCA, PLS(-DA), and OPLS(-DA)
opls-class: Class "opls"
plot: Plot Method for (O)PLS(-DA)
predict: Predict method for (O)PLS models
print: Print method for 'opls' objects
residuals: Residuals method for (O)PLS models
ropls-package: PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and...
sacurine: Analysis of the human adult urinary metabolome variations...
show: Show method for 'opls' objects
strF: Printed summary of an R object
tested: Tested method for (O)PLS models
toW4M: Exporting ExpressionSet instance into 3 tabulated files.