Graphs the output of a dimensional reduction technique (PCA by default). Cells are colored by their identity class.
DimPlot(object, reduction.use = "pca", dim.1 = 1, dim.2 = 2,
cells.use = NULL, pt.size = 3, do.return = FALSE, do.bare = FALSE,
cols.use = NULL, group.by = "ident", pt.shape = NULL,
do.hover = FALSE, data.hover = "ident", do.identify = FALSE,
do.label = FALSE, label.size = 1, no.legend = FALSE, no.axes = FALSE,
dark.theme = FALSE, ...)Seurat object
Which dimensionality reduction to use. Default is "pca", can also be "tsne", or "ica", assuming these are precomputed.
Dimension for x-axis (default 1)
Dimension for y-axis (default 2)
Vector of cells to plot (default is all cells)
Adjust point size for plotting
Return a ggplot2 object (default : FALSE)
Do only minimal formatting (default : FALSE)
Vector of colors, each color corresponds to an identity class. By default, ggplot assigns colors.
Group (color) cells in different ways (for example, orig.ident)
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.
Enable hovering over points to view information
Data to add to the hover, pass a character vector of features to add. Defaults to cell name and ident. Pass 'NULL' to clear extra information.
Opens a locator session to identify clusters of cells.
Whether to label the clusters
Sets size of labels
Setting to TRUE will remove the legend
Setting to TRUE will remove the axes
Use a dark theme for the plot
If do.return==TRUE, returns a ggplot2 object. Otherwise, only graphical output.