AverageExpression: Averaged feature expression by identity class

In atakanekiz/Seurat3.0: Tools for Single Cell Genomics

Description

Returns expression for an 'average' single cell in each identity class

Usage

AverageExpression(object, assay = NULL, features = NULL,
  return.seurat = FALSE, add.ident = NULL, use.scale = FALSE,
  use.counts = FALSE, verbose = TRUE, ...)

Arguments

object	Seurat object
assay	Which assay to use. Default is all assays.
features	Features to analyze. Default is all features in the assay.
return.seurat	Whether to return the data as a Seurat object. Default is FALSE.
add.ident	Place an additional label on each cell prior to averaging (very useful if you want to observe cluster averages, separated by replicate, for example).
use.scale	Use scaled values for gene expression
use.counts	Use count values for gene expression
verbose	Print messages and show progress bar
...	Arguments to be passed to methods such as CreateSeuratObject

Details

Output is in log-space when return.seurat = TRUE, otherwise it's in non-log space. Averaging is done in non-log space.

Value

Returns a matrix with genes as rows, identity classes as columns. If return.seurat is TRUE, returns an object of class Seurat.

Examples

head(AverageExpression(object = pbmc_small))

atakanekiz/Seurat3.0 documentation built on May 26, 2019, 2:33 a.m.