FeaturePlot: Visualize 'features' on a dimensional reduction plot
In atakanekiz/Seurat3.0: Tools for Single Cell Genomics

Description Usage Arguments Value Note See Also Examples

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 = c("lightgrey", "blue"), pt.size = NULL, min.cutoff = NA,
  max.cutoff = NA, reduction = NULL, split.by = NULL,
  shape.by = NULL, blend = FALSE, blend.threshold = 0.5,
  order = NULL, label = FALSE, label.size = 4, ncol = NULL,
  combine = TRUE, coord.fixed = FALSE)

`object`	Seurat object
`features`	Vector of features to plot
`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.
`pt.size`	Adjust point size for plotting
`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`
`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
`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.
`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)
`label`	Whether to label the clusters
`label.size`	Sets size of labels
`ncol`	Number of columns to combine multiple feature plots to, ignored if `split.by` is not `NULL`
`combine`	Combine plots into a single gg object; note that if TRUE; themeing will not work when plotting multiple features
`coord.fixed`	Plot cartesian coordinates with fixed aspect ratio