methodsDimReduction: Wrapper function for dimensionality reduction methods

In HannahVMeyer/DrStable: Estimating the stability of dimensionality reduction results

Description

Wrapper function for dimensionality reduction methods

Usage

methodsDimReduction(Y, ndim, distY = dist(Y, method = dist.method),
  dist.method = "euclidean", method = c("DiffusionMap", "DRR", "ICA",
  "LLE", "Isomap", "LaplacianEigenmap", "MDS", "PCA", "kPCA", "nMDS",
  "tSNE", "UMAP"), optN = NULL, verbose = FALSE, params = NULL)

Arguments

Y	\[N x P\] data matrix for which the dimensionality of P should be reduced
ndim	maximum dimensionality [integer] to retain in the data; large values can cause long computation times.
distY	[dist] object of class dist containing pairwise distances of Y used for methods DiffusionMap, Isomap, MDS and nMDS; if non specified, stats::dist with Euclidean distance applied to supplied Y.
dist.method	[character] method for computing the distance matrix; one of euclidean, maximum, manhattan, canberra, binary or minkowski; see dist for details.
method	Dimensionality reduction method [character] to be applied; one of DiffusionsMaps, DRR, ICA, LLE, Isomap, LaplacianEigenmap, MDS, PCA, kPCA, nMDS and tSNE.
optN	optimal number [integer] of neighbours to consider for dimensionality reduction; relevant for methods LLE, LaplacianEigenmaps, Isomap and tSNE.
verbose	[logical] If set, progress messages are printed to standard out.
params	[list] optional additional parameters for dimensionality reduction methods; see details.

Details

methodsDimReduction wraps around the following implementations of the dimensionality reduction methods it provides: * Diffusion Map: diffuse * Dimensionality reduction by regression (DRR): drr * Independent component analysis (ICA): fastICA * Local liner embedding (LLE): lle * Isomap: isomap * Laplacian Eigenmap: spec.emb and make.kNNG * Multi-dimensional scaling (MDS) : cmdscale * Principal component analysis (PCA): prcomp * Kernel PCA (kPCA): kpca * non-metrix MDS (nMDS): metaMDS * t- stochastic neighbourhood embedding (tSNE): Rtsne * Uniform manifold approximation and projection (umap): umap

Value

named list with dimensionality reduced phenotypes (reducedY) and object returned by specified dimensionality reduction method (results) with additional output, see details.

HannahVMeyer/DrStable documentation built on Jan. 29, 2021, 11:42 a.m.