kayla-jackson / concordexR

Compute the neighborhood consolidation matrix and identify SHRs

concordexR

The goal of concordexR is to replace UMAP as a clustering diagnostic.

Installation

This repository is not maintained. It has been moved to https://github.com/pachterlab/concordexR.

You can install the development version of concordexR from GitHub with:

# install.packages("devtools")
devtools::install_github("kayla-jackson/concordexR")

Example

This is a basic example using concordex:

library(concordexR)
library(BiocNeighbors)

g <- findKNN(iris[, seq_len(4)], k = 10)
#> Warning in (function (to_check, X, clust_centers, clust_info, dtype, nn, :
#> detected tied distances to neighbors, see ?'BiocNeighbors-ties'
res <- calculateConcordex(g$index, labels = iris$Species, k = 10, return.map = TRUE)

plotConcordexSim(res)

heatConcordex(res)