Scatter plot of single cell data
Creates a scatter plot of two features (typically feature expression), across a set of single cells. Cells are colored by their identity class. Pearson correlation between the two features is displayed above the plot.
FeatureScatter( object, feature1, feature2, cells = NULL, group.by = NULL, cols = NULL, pt.size = 1, shape.by = NULL, span = NULL, smooth = FALSE, combine = TRUE, slot = "data", plot.cor = TRUE, raster = NULL )
object |
Seurat object |
feature1 |
First feature to plot. Typically feature expression but can also be metrics, PC scores, etc. - anything that can be retreived with FetchData |
feature2 |
Second feature to plot. |
cells |
Cells to include on the scatter plot. |
group.by |
Name of one or more metadata columns to group (color) cells by (for example, orig.ident); pass 'ident' to group by identity class |
cols |
Colors to use for identity class plotting. |
pt.size |
Size of the points on the plot |
shape.by |
Ignored for now |
span |
Spline span in loess function call, if |
smooth |
Smooth the graph (similar to smoothScatter) |
combine |
Combine plots into a single |
slot |
Slot to pull data from, should be one of 'counts', 'data', or 'scale.data' |
plot.cor |
Display correlation in plot title |
raster |
Convert points to raster format, default is |
A ggplot object
data("pbmc_small") FeatureScatter(object = pbmc_small, feature1 = 'CD9', feature2 = 'CD3E')
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