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OmicsPLS (version 2.1.0)

Data Integration with Two-Way Orthogonal Partial Least Squares

Description

Performs the O2PLS data integration method for two datasets, yielding joint and data-specific parts for each dataset. The algorithm automatically switches to a memory-efficient approach to fit O2PLS to high dimensional data. It provides a rigorous and a faster alternative cross-validation method to select the number of components, as well as functions to report proportions of explained variation and to construct plots of the results. See the software article by el Bouhaddani et al (2018) , and Trygg and Wold (2003) . It also performs Sparse Group (Penalized) O2PLS, see Gu et al (2020) and cross-validation for the degree of sparsity.

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Version

Install

install.packages('OmicsPLS')

Monthly Downloads

256

Version

2.1.0

License

GPL-3

Maintainer

Said Bouhaddani

Last Published

April 1st, 2025

Functions in OmicsPLS (2.1.0)

print.o2m

Print function for O2PLS.
lambda_checker_group

Check if penalization parameters for groups satisfy input conditions
print.pre.o2m

Print function for O2PLS.
rmsep_combi

Symmetrized root MSE of Prediction
scores

Extract the scores from an O2PLS fit
print.summary.o2m

Prints the summary of an O2PLS fit
rmsep

Root MSE of Prediction
orth_vec

Orthogonalize a sparse loading vector with regard to a matrix
plot.o2m

Plot one or two loading vectors for class o2m
o2m_stripped2

Perform O2-PLS with two-way orthogonal corrections
orth

Orthogonalize a matrix
thresh_n

Soft threshholding a vector with respect to a number of variables
summary.o2m

Summary of an O2PLS fit
vnorm

Norm of a vector or columns of a matrix
thresh_n_gr

Soft threshholding a vector with respect to a number of groups
pow_o2m2

Power method for PLS2
pow_o2m

NIPALS method for PLS2
predict.o2m

Predicts X or Y
print.cvo2m

Cross-validate procedure for O2PLS
ssq

Calculate Sum of Squares
so2m_group

Perform Group Sparse O2PLS
err_back

Internal function for crossval_sparsity
cv_lambda_checker_group

Check if sparsity parameters satisfy input conditions in cross-validation functions
crossval_o2m

Cross-validate procedure for O2PLS
crossval_o2m_adjR2

Adjusted Cross-validate procedure for O2PLS
adjR2

Gridwise adjusted R2 for O2PLS
crossval_sparsity

Perform cross-validation to find the optimal number of variables/groups to keep for each joint component
impute_matrix

Impute missing values in a matrix
OmicsPLS-package

Data integration with O2PLS: Two-Way Orthogonal Partial Least Squares
input_checker

Check if matrices satisfy input conditions
cv_lambda_checker

Check if sparsity parameters satisfy input conditions in cross-validation functions
lambda_checker

Check if penalization parameters satisfy input conditions
loocv

K fold CV for O2PLS
loocv_combi

K-fold CV based on symmetrized prediction error
mse

Calculate mean squared difference
norm_vec

Norm of a vector
loadings

Extract the loadings from an O2PLS fit
o2m

Perform O2PLS data integration with two-way orthogonal corrections
o2m2

Perform O2-PLS with two-way orthogonal corrections
o2m_stripped

Perform O2-PLS with two-way orthogonal corrections