DimPlot: Dimensional reduction plot

In mrod0101/seurat: Tools for Single Cell Genomics

Description

Graphs the output of a dimensional reduction technique on a 2D scatter plot where each point is a cell and it's positioned based on the cell embeddings determined by the reduction technique. By default, cells are colored by their identity class (can be changed with the group.by parameter).

Usage

DimPlot(
  object,
  dims = c(1, 2),
  cells = NULL,
  cols = NULL,
  pt.size = NULL,
  reduction = NULL,
  group.by = NULL,
  split.by = NULL,
  shape.by = NULL,
  order = NULL,
  shuffle = FALSE,
  seed = 1,
  label = FALSE,
  label.size = 4,
  label.color = "black",
  label.box = FALSE,
  repel = FALSE,
  cells.highlight = NULL,
  cols.highlight = "#DE2D26",
  sizes.highlight = 1,
  na.value = "grey50",
  ncol = NULL,
  combine = TRUE,
  raster = NULL,
  raster.dpi = c(512, 512)
)

PCAPlot(object, ...)

TSNEPlot(object, ...)

UMAPPlot(object, ...)

Arguments

object	Seurat object
dims	Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions
cells	Vector of cells to plot (default is all cells)
cols	Vector of colors, each color corresponds to an identity class. This may also be a single character or numeric value corresponding to a palette as specified by brewer.pal.info. By default, ggplot2 assigns colors. We also include a number of palettes from the pals package. See DiscretePalette for details.
pt.size	Adjust point size for plotting
reduction	Which dimensionality reduction to use. If not specified, first searches for umap, then tsne, then pca
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
split.by	Name of a metadata column to split plot by; see FetchData for more details
shape.by	If NULL, all points are circles (default). You can specify any cell attribute (that can be pulled with FetchData) allowing for both different colors and different shapes on cells. Only applicable if raster = FALSE.
order	Specify the order of plotting for the idents. This can be useful for crowded plots if points of interest are being buried. Provide either a full list of valid idents or a subset to be plotted last (on top)
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.
label	Whether to label the clusters
label.size	Sets size of labels
label.color	Sets the color of the label text
label.box	Whether to put a box around the label text (geom_text vs geom_label)
repel	Repel labels
cells.highlight	A list of character or numeric vectors of cells to highlight. If only one group of cells desired, can simply pass a vector instead of a list. If set, colors selected cells to the color(s) in cols.highlight and other cells black (white if dark.theme = TRUE); will also resize to the size(s) passed to sizes.highlight
cols.highlight	A vector of colors to highlight the cells as; will repeat to the length groups in cells.highlight
sizes.highlight	Size of highlighted cells; will repeat to the length groups in cells.highlight
na.value	Color value for NA points when using custom scale
ncol	Number of columns for display when combining plots
combine	Combine plots into a single patchworked ggplot object. If FALSE, return a list of ggplot objects
raster	Convert points to raster format, default is NULL which automatically rasterizes if plotting more than 100,000 cells
raster.dpi	Pixel resolution for rasterized plots, passed to geom_scattermore(). Default is c(512, 512).
...	Extra parameters passed to DimPlot

Value

A patchworked ggplot object if combine = TRUE; otherwise, a list of ggplot objects

Note

For the old do.hover and do.identify functionality, please see HoverLocator and CellSelector, respectively.

See Also

FeaturePlot HoverLocator CellSelector FetchData

Examples

data("pbmc_small")
DimPlot(object = pbmc_small)
DimPlot(object = pbmc_small, split.by = 'ident')

mrod0101/seurat documentation built on March 2, 2022, 12:17 a.m.