loadings (version 0.5.1)

multipls_loading: Multiset partial least squares loading

Description

This function computes multiset partial least squares (PLS) loading from the result of the "multipls_geigen" function.

Usage

multipls_loading(multipls)

Value

The return value is a list object that contains the following elements:

Score : A list of matrix with Multiset PLS score for auxiliary variable in each column for each dataset

R : A list of matrix with Multiset PLS loadings in each column for each dataset

p.value : A list of matrix with p-value of multiset PLS loading in each column for each dataset

Arguments

multipls

The following variables (P,T,Q and U) are included in the multipls object.

P : A list of matrix with Multiset PLS coefficients for the explanatory variables in each column for each dataset

T : A list of matrix with Multiset PLS scores for the explanatory variables in each column for each dataset

Q : A matrix with Multiset PLS coefficients for the response variable in each column

U : A matrix with Multiset PLS scores for the response variable in each column

tau : Matrix for strength parameter of the connection between omics datasets or between omics dataset and group information.

Author

Hiroyuki Yamamoto

Details

The multiset PLS loading and the p-value by statistical hypothesis testing is added to the multipls object returned by the "multipls_geigen" function in this package.

References

Yamamoto H. (2022) Multiset partial least squares with rank order of groups for integrating multi-omics data, bioRxiv.

Examples

data(whhl)
X <- whhl$X
Y <- whhl$Y
tau <- whhl$tau

multipls <- multipls_geigen(X,Y,tau)

multipls <- multipls_loading(multipls)
multipls$loading$R
multipls$loading$p.value