gammaPlot: UMAP visualization of clusters

In aarkatkar/gelClust: Clustering and pathway analysis using exponential distributions

UMAP visualization of clusters

Description

Plot features using Uniform Manifold Approximation and Projection and colored according to the gammaCluster function. This is useful for verifying that the gamma clustering model accurately characterizes the underlying structure of the correlations.

Usage

gammaPlot(gm, clusters)

Arguments

gm	the output of the gelMatrix function
clusters	a numeric vector of cluster labels, usually obtained from labels attribute of the gammaCluster function

Value

a plot of features placed according to UMAP and colored according to gamma clustering.

Author(s)

Anooj Arkatkar

References

McInnes, L., Healy, J., & Melville, J. (2018). Umap: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426.

See Also

gammaCluster

Examples

data(foldChange)
gm <- gelMatrix(foldChange)
clust <- gammaCluster(gm, 7)
gammaPlot(gm, clust$labels)

aarkatkar/gelClust documentation built on May 6, 2022, 12:24 a.m.