Seurat (version 2.1.0)

FeaturePlot: Visualize 'features' on a dimensional reduction plot

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, min.cutoff = NA, max.cutoff = NA,
  dim.1 = 1, dim.2 = 2, cells.use = NULL, pt.size = 1,
  cols.use = c("yellow", "red"), pch.use = 16, overlay = FALSE,
  do.hover = FALSE, data.hover = "ident", do.identify = FALSE,
  reduction.use = "tsne", use.imputed = FALSE, nCol = NULL,
  no.axes = FALSE, no.legend = TRUE, dark.theme = FALSE,
  do.return = FALSE)

Arguments

object

Seurat object

features.plot

Vector of features to plot

min.cutoff

Vector of minimum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 1, 10)

max.cutoff

Vector of maximum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 1, 10)

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

overlay

Plot two features overlayed one on top of the other

do.hover

Enable hovering over points to view information

data.hover

Data to add to the hover, pass a character vector of features to add. Defaults to cell name and identity. Pass 'NULL' to remove extra data.

do.identify

Opens a locator session to identify clusters of cells

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

no.legend

Remove legend from the graph. Default is TRUE.

dark.theme

Plot in a dark theme

do.return

return the ggplot2 object

Value

No return value, only a graphical output

Examples

# NOT RUN {
FeaturePlot(object = pbmc_small, features.plot = 'PC1')

# }