getComMembership: Get clusters by community detection on approximate nearest...

In JEFworks/MUDAN: Multi-sample Unified Discriminant ANalysis

Description

Group cells into clusters based on graph-based community detection on approximate nearest neighbors

Usage

getComMembership(mat, k, method = igraph::cluster_walktrap, verbose = TRUE,
  details = FALSE)

Arguments

mat	Matrix of cells as columns. Features as rows (such as PCs).
k	K-nearest neighbor parameter.
method	Community detection method from igraph. (default: igraph::cluster_walktrap)
verbose	Verbosity (default: TRUE)
details	Whether to return just community annotation or entended details including graph and graph modularity

Value

Vector of community annotations

Examples

{
data(pbmcA)
cd <- pbmcA[, 1:500]
mat <- cleanCounts(cd)
mat <- normalizeVariance(mat)
pcs <- getPcs(mat)
com <- getComMembership(pcs, k=30)
}

JEFworks/MUDAN documentation built on June 19, 2021, 6:46 a.m.