plot_hexbin_feature {schex} | R Documentation |
Plot of external feature expression of single cells in bivariate hexagon cells.
plot_hexbin_feature( sce, mod, type, feature, action, title = NULL, xlab = NULL, ylab = NULL ) ## S4 method for signature 'SingleCellExperiment' plot_hexbin_feature( sce, mod, type, feature, action, title = NULL, xlab = NULL, ylab = NULL ) ## S4 method for signature 'Seurat' plot_hexbin_feature( sce, mod, type, feature, action, title = NULL, xlab = NULL, ylab = NULL )
sce |
A |
mod |
A string referring to the name of the alternative object in a
|
type |
A string referring to the type of assay in the
|
feature |
A string referring to the name of one external feature. |
action |
A strings pecifying how meta data of observations in
binned hexagon cells are to be summarized. Possible actions are
|
title |
A string containing the title of the plot. |
xlab |
A string containing the title of the x axis. |
ylab |
A string containing the title of the y axis. |
This function plots the expression of any feature in the hexagon
cell representation calculated with make_hexbin
. The chosen
gene expression is summarized by one of four actions prop_0
,
mode
, mean
and median
:
prop_0
Returns the proportion of observations in the bin greater than 0. The associated meta data column needs to be numeric.
mode
Returns the mode of the observations in the bin. The associated meta data column needs to be numeric.
mean
Returns the mean of the observations in the bin. The associated meta data column needs to be numeric.
median
Returns the median of the observations in the bin. The associated meta data column needs to be numeric.
A ggplot2{ggplot}
object.
SingleCellExperiment
: Plot of gene expression into hexagon
cell for SingleCellExperiment object.
Seurat
: Plot of gene expression into hexagon cell
for Seurat object.
# For Seurat object library(Seurat) data("pbmc_small") pbmc_small <- make_hexbin(pbmc_small, 10, dimension_reduction = "PCA") protein <- matrix(rnorm(10* ncol(pbmc_small)), ncol=ncol(pbmc_small)) rownames(protein) <- paste0("A", seq(1,10,1)) colnames(protein) <- colnames(pbmc_small) pbmc_small[["ADT"]] <- CreateAssayObject(counts = protein) pbmc_small <- make_hexbin(pbmc_small, 10, dimension_reduction = "PCA") plot_hexbin_feature(pbmc_small, type="counts", mod="ADT", feature="A1", action="prop_0")