FeaturePlot: Visualize 'features' on a dimensional reduction plot

In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description

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

Usage

FeaturePlot(object, features.plot, dim.1 = 1, dim.2 = 2, cells.use = NULL,
  pt.size = 1, cols.use = c("yellow", "red"), pch.use = 16,
  reduction.use = "tsne", use.imputed = FALSE, nCol = NULL,
  no.axes = FALSE)

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)
cells.use	Vector of cells to plot (default is all cells)
pt.size	Adjust point size for plotting
cols.use	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.
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.
use.imputed	Use imputed values for gene expression (default is FALSE)
nCol	Number of columns to use when plotting multiple features.
no.axes	Remove axis labels

Value

No return value, only a graphical output

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