loadings (version 0.5.1)

ospca_loading: Orthogonal smoothed principal component loading

Description

This function computes orthogonals smoothed principal component (OS-PC) loading from the result of the "os_pca" function. This is also wrapper function of pls_loading function.

Usage

ospca_loading(ospca)

Value

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

R : OS-PCA loading (Correlation coefficient between OS-PC score of auxiliary variable and each variables in data matrix.)

p.value : p-value of OS-PCA loading

Arguments

ospca

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

P : A matrix with OS-PC loading in each column

T : A matrix with OS-PC score in each column

MT : A matrix with averaging OS-PC score for repeated data in each column (If not for repeated data, the matrix MT equals to the matrix T)

Q : A matrix with OS-PC loading for auxiliary variable in each column

U : A matrix with OS-PC score for auxiliary variable in each column

Author

Hiroyuki Yamamoto

Details

The OS-PC loading and the p-value by statistical hypothesis testing is added to the ospca object returned by the "os-pca" function.

References

Yamamoto H., Nakayama Y., Tsugawa H. (2021) OS-PCA: Orthogonal Smoothed Principal Component Analysis Applied to Metabolome Data, Metabolites, 11(3):149.

Examples

# metabolic turnover data
data(turnover)
X <- turnover$X
D <- turnover$D

ospca <- os_pca(X,D,0.999)

ospca <- ospca_loading(ospca)
ospca$loading$R
ospca$loading$p.value

# metabolome data

data(greentea)
X <- greentea$X
D <- greentea$D
M <- greentea$M

ospca <- os_pca(X,D,0.1,M)

ospca <- ospca_loading(ospca)
ospca$loading$R
ospca$loading$p.value