Draws a ridge plot of single cell data (gene expression, metrics, PC scores, etc.)
Usage
RidgePlot(
object,
features,
cols = NULL,
idents = NULL,
sort = FALSE,
assay = NULL,
group.by = NULL,
y.max = NULL,
same.y.lims = FALSE,
log = FALSE,
ncol = NULL,
slot = deprecated(),
layer = "data",
stack = FALSE,
combine = TRUE,
fill.by = NULL
)Arguments
- object
Seurat object
- features
Features to plot (gene expression, metrics, PC scores, anything that can be retreived by FetchData)
- cols
Colors to use for plotting
- idents
Which classes to include in the plot (default is all)
- sort
Sort identity classes (on the x-axis) by the average expression of the attribute being potted, can also pass 'increasing' or 'decreasing' to change sort direction
- assay
Name of assay to use, defaults to the active assay
- group.by
Group (color) cells in different ways (for example, orig.ident)
- y.max
Maximum y axis value
- same.y.lims
Set all the y-axis limits to the same values
- log
plot the feature axis on log scale
- ncol
Number of columns if multiple plots are displayed
- slot
Slot to pull expression data from (e.g. "counts" or "data")
- layer
Layer to pull expression data from (e.g. "counts" or "data")
- stack
Horizontally stack plots for each feature
- combine
Combine plots into a single
patchworkedggplot object. IfFALSE, return a list of ggplot- fill.by
Color violins/ridges based on either 'feature' or 'ident'
Value
A patchworked ggplot object if
combine = TRUE; otherwise, a list of ggplot objects
Examples
data("pbmc_small")
RidgePlot(object = pbmc_small, features = 'PC_1')