Visualize 'features' on a dimensional reduction plot

Colors single cells on a dimensional reduction plot according to a 'feature' (i.e. gene expression, PC scores, number of genes detected, etc.)

FeaturePlot(
  object,
  features,
  dims = c(1, 2),
  cells = NULL,
  cols = if (blend) {     c("lightgrey", "#ff0000", "#00ff00") } else {    
    c("lightgrey", "blue") },
  pt.size = NULL,
  order = FALSE,
  min.cutoff = NA,
  max.cutoff = NA,
  reduction = NULL,
  split.by = NULL,
  keep.scale = "feature",
  shape.by = NULL,
  slot = "data",
  blend = FALSE,
  blend.threshold = 0.5,
  label = FALSE,
  label.size = 4,
  label.color = "black",
  repel = FALSE,
  ncol = NULL,
  coord.fixed = FALSE,
  by.col = TRUE,
  sort.cell = NULL,
  interactive = FALSE,
  combine = TRUE,
  raster = NULL,
  raster.dpi = c(512, 512)
)

Arguments

object	Seurat object
features	Vector of features to plot. Features can come from: An Assay feature (e.g. a gene name - "MS4A1") A column name from meta.data (e.g. mitochondrial percentage - "percent.mito") A column name from a DimReduc object corresponding to the cell embedding values (e.g. the PC 1 scores - "PC_1")
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	The two colors to form the gradient over. Provide as string vector with the first color corresponding to low values, the second to high. Also accepts a Brewer color scale or vector of colors. Note: this will bin the data into number of colors provided. When blend is TRUE, takes anywhere from 1-3 colors: 1 color: Treated as color for double-negatives, will use default colors 2 and 3 for per-feature expression 2 colors: Treated as colors for per-feature expression, will use default color 1 for double-negatives 3+ colors: First color used for double-negatives, colors 2 and 3 used for per-feature expression, all others ignored
pt.size	Adjust point size for plotting
order	Boolean determining whether to plot cells in order of expression. Can be useful if cells expressing given feature are getting buried.
min.cutoff, max.cutoff	Vector of minimum and maximum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10')
reduction	Which dimensionality reduction to use. If not specified, first searches for umap, then tsne, then pca
split.by	A factor in object metadata to split the feature plot by, pass 'ident' to split by cell identity'; similar to the old FeatureHeatmap
keep.scale	How to handle the color scale across multiple plots. Options are: "feature" (default; by row/feature scaling): The plots for each individual feature are scaled to the maximum expression of the feature across the conditions provided to 'split.by'. "all" (universal scaling): The plots for all features and conditions are scaled to the maximum expression value for the feature with the highest overall expression. NULL (no scaling): Each individual plot is scaled to the maximum expression value of the feature in the condition provided to 'split.by'. Be aware setting NULL will result in color scales that are not comparable between plots.
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.
slot	Which slot to pull expression data from?
blend	Scale and blend expression values to visualize coexpression of two features
blend.threshold	The color cutoff from weak signal to strong signal; ranges from 0 to 1.
label	Whether to label the clusters
label.size	Sets size of labels
label.color	Sets the color of the label text
repel	Repel labels
ncol	Number of columns to combine multiple feature plots to, ignored if split.by is not NULL
coord.fixed	Plot cartesian coordinates with fixed aspect ratio
by.col	If splitting by a factor, plot the splits per column with the features as rows; ignored if blend = TRUE
sort.cell	Redundant with order. This argument is being deprecated. Please use order instead.
interactive	Launch an interactive FeaturePlot
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

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

DimPlot HoverLocator CellSelector

Examples

data("pbmc_small")
FeaturePlot(object = pbmc_small, features = 'PC_1')