plot_density {Nebulosa} | R Documentation |
Plot gene-weighted 2D kernel density
plot_density( object, features, slot = NULL, joint = FALSE, reduction = NULL, dims = c(1, 2), method = c("ks", "wkde"), adjust = 1, size = 1, shape = 16, combine = TRUE, pal = "viridis", ... ) ## S4 method for signature 'Seurat' plot_density( object, features, slot = NULL, joint = FALSE, reduction = NULL, dims = c(1, 2), method = c("ks", "wkde"), adjust = 1, size = 1, shape = 16, combine = TRUE, pal = "viridis", ... ) ## S4 method for signature 'SingleCellExperiment' plot_density( object, features, slot = NULL, joint = FALSE, reduction = NULL, dims = c(1, 2), method = c("ks", "wkde"), adjust = 1, size = 1, shape = 16, combine = TRUE, pal = "viridis", ... )
object |
Seurat or SingleCellExperiment object |
features |
Features (e.g. genes) to visualize |
slot |
Type of data: |
joint |
Return joint density plot? By default |
reduction |
Name of the reduction to visualize. If not provided, last computed reduction is visualized |
dims |
Vector of length 2 specifying the dimensions to be plotted. By default, the first two dimensions are considered. |
method |
Kernel density estimation method:
|
adjust |
Numeric value to adjust to bandwidth. Default: 1. Not available
for |
size |
Size of the geom to be plotted (e.g. point size) |
shape |
Shape of the geom to be plotted |
combine |
Create a single plot? If |
pal |
String specifying the viridis color palette to use. |
... |
Further scale arguments passed to scale_color_viridis_c Options:
|
A scatterplot from a given reduction showing the gene-weighted density
Seurat
: Plot gene-weighted 2D kernel density
SingleCellExperiment
: Plot gene-weighted 2D kernel density
Jose Alquicira-Hernandez
data <- SeuratObject::pbmc_small plot_density(data, "CD3E")