pl_dimplot: Dimensional reduction plot

In zzwch/convgene: This package is designed to conveniently convert gene between human and mouse.

Description

Enhanced DimPlot of Seurat v3

Usage

pl_dimplot(
  object,
  group_by,
  shape_by = NULL,
  ncol = 2,
  slot = "data",
  subset_by = NULL,
  subset_groups = NULL,
  subset_cells = NULL,
  reduction = "umap",
  dims = c(1, 2),
  pt.size = 1,
  cols = scanpy_colors$default_64
)

Arguments

object	Seurat object
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 You can also plot features with gradient cols.
shape_by	one column name to control point shape
ncol	Number of columns for display when faceting plots
slot	FetchData of features from which slot.
subset_by	enhanced option, subset cells by the colname.
subset_groups	enhanced option, subset cells of these categories.
subset_cells	A vector of cell names. if not NULL, subset these cells, otherwise use subset_by and subset_groups
reduction	Which dimensionality reduction to use. e.g. umap, tsne, pca
dims	Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions
pt.size	Adjust point size for plotting
cols	Vector of colors, each color corresponds to an identity class.

Value

a ggplot object

zzwch/convgene documentation built on July 11, 2021, 9:41 a.m.