Seurat (version 2.1.0)

MergeSeurat: Merge Seurat Objects

Description

Merge two Seurat objects

Usage

MergeSeurat(object1, object2, project = NULL, min.cells = 0,
  min.genes = 0, is.expr = 0, do.normalize = TRUE, scale.factor = 10000,
  do.scale = FALSE, do.center = FALSE, names.field = 1,
  names.delim = "_", save.raw = TRUE, add.cell.id1 = NULL,
  add.cell.id2 = NULL)

Arguments

object1

First Seurat object to merge

object2

Second Seurat object to merge

project

Project name (string)

min.cells

Include genes with detected expression in at least this many cells

min.genes

Include cells where at least this many genes are detected

is.expr

Expression threshold for 'detected' gene

do.normalize

Normalize the data after merging. Default is TRUE. If set, will perform the same normalization strategy as stored for the first object

scale.factor

If normalizing on the cell level, this sets the scale factor.

do.scale

In [e-mail], perform row-scaling (gene-based z-score). FALSE by default, so run ScaleData after merging.

do.center

In [e-mail], perform row-centering (gene-based centering). FALSE by default

names.field

For the initial identity class for each cell, choose this field from the cell's column name

names.delim

For the initial identity class for each cell, choose this delimiter from the cell's column name

save.raw

TRUE by default. If FALSE, do not save the unmodified data in [e-mail] which will save memory downstream for large datasets

add.cell.id1

String to be appended to the names of all cells in object1

add.cell.id2

String to be appended to the names of all cells in object2

Value

Merged Seurat object

Examples

# NOT RUN {
# Split pbmc_small for this example
pbmc1 <- SubsetData(object = pbmc_small, cells.use = [e-mail][1:40])
pbmc1
pbmc2 <- SubsetData(object = pbmc_small, cells.use = [e-mail][41:80])
pbmc2
# Merge pbmc1 and pbmc2 into one Seurat object
pbmc_merged <- MergeSeurat(object1 = pbmc1, object2 = pbmc2)
pbmc_merged

# }