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, shuffle = FALSE, seed = 1, group.by = NULL, cols = NULL, pt.size = 1, shape.by = NULL, span = NULL, smooth = FALSE, combine = TRUE, slot = "data", plot.cor = TRUE, raster = NULL, raster.dpi = c(512, 512), jitter = TRUE )
| 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. |
| shuffle | Whether to randomly shuffle the order of points. This can be useful for crowded plots if points of interest are being buried. (default is FALSE) |
| seed | Sets the seed if randomly shuffling the order of points. |
| 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 |
| raster.dpi | Pixel resolution for rasterized plots, passed to geom_scattermore(). Default is c(512, 512). |
| jitter | Jitter for easier visualization of crowded points |
A ggplot object