Split_FeatureScatter(
seurat_object,
feature1 = NULL,
feature2 = NULL,
split.by = NULL,
group.by = NULL,
colors_use = NULL,
pt.size = NULL,
aspect_ratio = NULL,
title_size = 15,
num_columns = NULL,
raster = NULL,
raster.dpi = c(512, 512),
ggplot_default_colors = FALSE,
color_seed = 123,
...
)
Seurat object name.
First feature to plot.
Second feature to plot.
Feature to split plots by (i.e. "orig.ident").
Name of one or more metadata columns to group (color) cells by (for example, orig.ident). Use 'ident' to group.by active.ident class.
color for the points on plot.
Adjust point size for plotting.
Control the aspect ratio (y:x axes ratio length). Must be numeric value; Default is NULL.
size for plot title labels.
number of columns in final layout plot.
Convert points to raster format. Default is NULL which will rasterize by default if greater than 100,000 cells.
Pixel resolution for rasterized plots, passed to geom_scattermore(). Default is c(512, 512).
logical. If colors_use = NULL
, Whether or not to return plot using
default ggplot2 "hue" palette instead of default "polychrome" or "varibow" palettes.
random seed for the "varibow" palette shuffle if colors_use = NULL
and number of
groups plotted is greater than 36. Default = 123.
Extra parameters passed to FeatureScatter
.
A ggplot object
if (FALSE) {
# Function now DEPRECATED.
library(Seurat)
pbmc_small$sample_id <- sample(c("sample1", "sample2"), size = ncol(pbmc_small), replace = TRUE)
# OLD Code
Split_FeatureScatter(seurat_object = pbmc_small, feature1 = "nCount_RNA", feature2 = "nFeature_RNA",
split.by = "sample_id")
# NEW Code
FeatureScatter_scCustom(seurat_object = pbmc_small, feature1 = "nCount_RNA",
feature2 = "nFeature_RNA", split.by = "sample_id")
}