plot_hexbin_bivariate {schex} | R Documentation |
Plot of feature expression and uncertainty of single cells in bivariate hexagon cells.
plot_hexbin_bivariate( sce, mod = "RNA", type, feature, fan = FALSE, title = NULL, xlab = NULL, ylab = NULL )
sce |
A |
mod |
A string referring to the name of the modality used for plotting.
For RNA modality use "RNA". For other modalities use name of alternative
object for the |
type |
A string referring to the type of assay in the
|
feature |
A string referring to the name of one feature. |
fan |
Logical indicating whether to plot uncertainty surpressing palette. |
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 mean expression and a measure of uncertainty
of any feature in the hexagon cell representation calculated with
make_hexbin
using a bivariate scale. When fan=FALSE
,
the standard deviation and the mean expression are plotted. When
fan=TRUE
, the mean expression and coefficient of variation are
calculated. The coefficient of variation is converted to a percentage of
uncertainty. When using fan=TRUE
the raw count data should be used.
In order to enable the calculation of the coefficient of variation a
pseduo-count of 1 is added to every count.
To access the data that has been integrated in the
Seurat-class
object specifiy mod="integrated"
.
A ggplot2{ggplot}
object.
# For Seurat object library(Seurat) data("pbmc_small") pbmc_small <- make_hexbin(pbmc_small, 10, dimension_reduction = "PCA") plot_hexbin_bivariate(pbmc_small, type="counts", feature="CD3D") plot_hexbin_bivariate(pbmc_small, type="counts", feature="CD3D", fan=TRUE)