adaptiveGPCA-package: adaptiveGPCA: A package for structured dimensionality...

In adaptiveGPCA: Adaptive Generalized PCA

adaptiveGPCA: A package for structured dimensionality reduction

Description

This package implements the methods for structured dimensionality reduction described in Fukuyama, J. (2017). The general idea is to obtain a low-dimensional representation of the data, similar to that given by PCA, which incorporates side information about the relationships between the variables. The output is similar to a PCA biplot, but the variable loadings are regularized so that similar variables are encouraged to have similar loadings on the principal axes.

Details

There are two main ways of using this package. The function adaptivegpca will choose how much to regularize the variables according to the similarities between them, while the function gpcaFullFamily produces analogous output for a range of regularization parameters. With this function, the results for the different regularization parameters are inspected with the visualizeFullFamily function, and the desired parameter is chosen manually.

The package also contains functionality to integrate with phyloseq: the function processPhyloseq takes a phyloseq object and creates the inputs necessary to perform adaptive gPCA on a microbiome dataset including information about the phylogenetic relationships between the bacteria.

adaptiveGPCA documentation built on Dec. 8, 2022, 5:12 p.m.