Seurat (version 1.2.1)

feature.heatmap: Vizualization of multiple features

Description

Similar to feature.plot, however, also splits the plot by visualizing each identity class separately.

Usage

feature.heatmap(object, features.plot, dim.1 = 1, dim.2 = 2, idents.use = NULL, pt.size = 2, cols.use = rev(heat.colors(10)), pch.use = 16, reduction.use = "tsne")

Arguments

object

Seurat object

features.plot

Vector of features to plot

dim.1

Dimension for x-axis (default 1)

dim.2

Dimension for y-axis (default 2)

idents.use

Which identity classes to display (default is all identity classes)

pt.size

Adjust point size for plotting

cols.use

Ordered vector of colors to use for plotting. Default is heat.colors(10).

pch.use

Pch for plotting

reduction.use

Which dimensionality reduction to use. Default is "tsne", can also be "pca", or "ica", assuming these are precomputed.

Value

No return value, only a graphical output

Details

Particularly useful for seeing if the same groups of cells co-exhibit a common feature (i.e. co-express a gene), even within an identity class. Best understood by example.