CellChat (version 1.0.0)

netClustering: Classification learning of the signaling networks

Description

Classification learning of the signaling networks

Usage

netClustering(
  object,
  slot.name = "netP",
  type = c("functional", "structural"),
  comparison = NULL,
  k = NULL,
  methods = "kmeans",
  do.plot = TRUE,
  fig.id = NULL,
  do.parallel = TRUE,
  nCores = 4,
  k.eigen = NULL
)

Arguments

object

CellChat object

slot.name

the slot name of object that is used to compute centrality measures of signaling networks

type

"functional","structural"

comparison

a numerical vector giving the datasets for comparison. No need to define for a single dataset. Default are all datasets when object is a merged object

k

the number of signaling groups when running kmeans

methods

the methods for clustering: "kmeans" or "spectral"

do.plot

whether showing the eigenspectrum for inferring number of clusters; Default will save the plot

fig.id

add a unique figure id when saving the plot

do.parallel

whether doing parallel when inferring the number of signaling groups when running kmeans

nCores

number of workers when doing parallel

k.eigen

the number of eigenvalues used when doing spectral clustering

Value