rankSimilarity: Rank the similarity of the shared signaling pathways based on...

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

Rank the similarity of the shared signaling pathways based on their joint manifold learning

Description

Rank the similarity of the shared signaling pathways based on their joint manifold learning

Usage

rankSimilarity(
  object,
  slot.name = "netP",
  type = c("functional", "structural"),
  comparison1 = NULL,
  comparison2 = c(1, 2),
  x.rotation = 90,
  title = NULL,
  color.use = NULL,
  bar.w = NULL,
  font.size = 8
)

Arguments

object	CellChat object
slot.name	the slot name of object that is used to compute centrality measures of signaling networks
type	"functional","structural"
comparison1	a numerical vector giving the datasets for comparison. This should be the same as 'comparison' in 'computeNetSimilarityPairwise'
comparison2	a numerical vector with two elements giving the datasets for comparison. If there are more than 2 datasets defined in 'comparison1', 'comparison2' can be defined to indicate which two datasets used for computing the distance. e.g., comparison2 = c(1,3) indicates the first and third datasets defined in 'comparison1' will be used for comparison.
x.rotation	rotation of x-labels
title	main title of the plot
color.use	defining the color
bar.w	the width of bar plot
font.size	font size

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