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#' adaptiveGPCA: A package for structured dimensionality reduction
#'
#' This package implements the methods for structured dimensionality
#' reduction described in
#' \href{https://arxiv.org/abs/1702.00501}{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.
#'
#' There are two main ways of using this package. The function
#' \code{\link{adaptivegpca}} will choose how much to regularize the
#' variables according to the similarities between them, while the
#' function \code{\link{gpcaFullFamily}} produces analogous output for
#' a range of regularization parameters. With this function, the
#' results for the different regularization parameters are inspected
#' with the \code{\link{visualizeFullFamily}} function, and the
#' desired parameter is chosen manually.
#'
#' The package also contains functionality to integrate with phyloseq:
#' the function \code{\link{processPhyloseq}} takes a
#' \code{\link[phyloseq]{phyloseq}} object and creates the inputs
#' necessary to perform adaptive gPCA on a microbiome dataset
#' including information about the phylogenetic relationships between
#' the bacteria.
#'
#'
#' @docType package
#' @name adaptiveGPCA-package
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