2D visualization of the joint manifold learning of signaling networks from two datasets
netVisual_embeddingPairwise(
object,
slot.name = "netP",
type = c("functional", "structural"),
comparison = NULL,
color.use = NULL,
point.shape = NULL,
pathway.remove = NULL,
pathway.remove.show = TRUE,
dot.size = c(2, 6),
label.size = 2.5,
dot.alpha = 0.5,
xlabel = "Dim 1",
ylabel = "Dim 2",
title = NULL,
do.label = T,
show.legend = T,
show.axes = T
)CellChat object
the slot name of object that is used to compute centrality measures of signaling networks
"functional","structural"
a numerical vector giving the datasets for comparison. Default are all datasets when object is a merged object
defining the color for each cell group
a numeric vector giving the point shapes. By default point.shape <- c(21, 0, 24, 23, 25, 10, 12), see available shapes at http://www.sthda.com/english/wiki/r-plot-pch-symbols-the-different-point-shapes-available-in-r
a character vector defining the signaling to remove
whether show the removed signaling names
a range defining the size of the symbol
font size of the text
transparency
label of x-axis
label of y-axis
main title of the plot
label the each point
whether show the legend
whether show the axes