netClustering: Classification learning of the signaling networks

In sqjin/CellChat: Inference and analysis of cell-cell communication from single-cell and spatial transcriptomics data

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

sqjin/CellChat documentation built on Nov. 10, 2023, 4:29 a.m.