ColorDimSplit: Color dimensional reduction plot by tree split

In Seurat: Tools for Single Cell Genomics

Color dimensional reduction plot by tree split

Description

Returns a DimPlot colored based on whether the cells fall in clusters to the left or to the right of a node split in the cluster tree.

Usage

ColorDimSplit(
  object,
  node,
  left.color = "red",
  right.color = "blue",
  other.color = "grey50",
  ...
)

Arguments

object	Seurat object
node	Node in cluster tree on which to base the split
left.color	Color for the left side of the split
right.color	Color for the right side of the split
other.color	Color for all other cells
...	Arguments passed on to DimPlot 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).

Value

Returns a DimPlot

See Also

DimPlot

Examples

if (requireNamespace("ape", quietly = TRUE)) {
  data("pbmc_small")
  pbmc_small <- BuildClusterTree(object = pbmc_small, verbose = FALSE)
  PlotClusterTree(pbmc_small)
  ColorDimSplit(pbmc_small, node = 5)
}

Seurat documentation built on May 2, 2022, 9:05 a.m.