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OmicsPLS (version 2.0.2)

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

504

Version

2.0.2

License

GPL-3

Maintainer

Said Bouhaddani

Last Published

May 19th, 2021

Functions in OmicsPLS (2.0.2)

norm_vec

Norm of a vector
scores

Extract the scores from an O2PLS fit
rmsep_combi

Symmetrized root MSE of Prediction
pow_o2m2

Power method for PLS2
input_checker

Check if matrices satisfy input conditions
crossval_o2m

Cross-validate procedure for O2PLS
o2m2

Perform O2-PLS with two-way orthogonal corrections
orth_vec

Orthogonalize a sparse loading vector with regard to a matrix
o2m_stripped

Perform O2-PLS with two-way orthogonal corrections
plot.o2m

Plot one or two loading vectors for class o2m
crossval_o2m_adjR2

Adjusted Cross-validate procedure for O2PLS
summary.o2m

Summary of an O2PLS fit
crossval_sparsity

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

Calculate Sum of Squares
so2m_group

Perform Group Sparse O2PLS
cv_lambda_checker

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

K fold CV for O2PLS
loadings

Extract the loadings from an O2PLS fit
orth

Orthogonalize a matrix
o2m_stripped2

Perform O2-PLS with two-way orthogonal corrections
print.pre.o2m

Print function for O2PLS.
print.o2m

Print function for O2PLS.
lambda_checker

Check if penalization parameters satisfy input conditions
mse

Calculate mean squared difference
loocv_combi

K-fold CV based on symmetrized prediction error
cv_lambda_checker_group

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

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

Prints the summary of an O2PLS fit
predict.o2m

Predicts X or Y
err_back

Internal function for crossval_sparsity
rmsep

Root MSE of Prediction
vnorm

Norm of a vector or columns of a matrix
print.cvo2m

Cross-validate procedure for O2PLS
thresh_n_gr

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

Soft threshholding a vector with respect to a number of variables
adjR2

Gridwise adjusted R2 for O2PLS
OmicsPLS

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

Impute missing values in a matrix
pow_o2m

NIPALS method for PLS2
o2m

Perform O2PLS data integration with two-way orthogonal corrections