FeatureHeatmap: Vizualization of multiple features
In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description Usage Arguments Details Value

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

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FeatureHeatmap(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")

`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.

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.

No return value, only a graphical output

nukappa/seurat_v2 documentation built on May 24, 2019, 9:57 a.m.