CreateSeuratObject: Create a 'Seurat' object

In SeuratObject: Data Structures for Single Cell Data

Create a Seurat object

Description

Create a Seurat object from raw data

Usage

CreateSeuratObject(
  counts,
  assay = "RNA",
  names.field = 1,
  names.delim = "_",
  meta.data = NULL,
  project = "CreateSeuratObject",
  ...
)

## Default S3 method:
CreateSeuratObject(
  counts,
  assay = "RNA",
  names.field = 1L,
  names.delim = "_",
  meta.data = NULL,
  project = "SeuratProject",
  min.cells = 0,
  min.features = 0,
  ...
)

## S3 method for class 'Assay'
CreateSeuratObject(
  counts,
  assay = "RNA",
  names.field = 1L,
  names.delim = "_",
  meta.data = NULL,
  project = "SeuratProject",
  ...
)

## S3 method for class 'Assay5'
CreateSeuratObject(
  counts,
  assay = "RNA",
  names.field = 1L,
  names.delim = "_",
  meta.data = NULL,
  project = "SeuratProject",
  ...
)

Arguments

counts	Either a matrix-like object with unnormalized data with cells as columns and features as rows or an Assay-derived object
assay	Name of the initial assay
names.field	For the initial identity class for each cell, choose this field from the cell's name. E.g. If your cells are named as BARCODE_CLUSTER_CELLTYPE in the input matrix, set names.field to 3 to set the initial identities to CELLTYPE.
names.delim	For the initial identity class for each cell, choose this delimiter from the cell's column name. E.g. If your cells are named as BARCODE-CLUSTER-CELLTYPE, set this to “-” to separate the cell name into its component parts for picking the relevant field.
meta.data	Additional cell-level metadata to add to the Seurat object. Should be a data.frame where the rows are cell names and the columns are additional metadata fields. Row names in the metadata need to match the column names of the counts matrix.
project	Project name for the Seurat object
...	Arguments passed to other methods
min.cells	Include features detected in at least this many cells. Will subset the counts matrix as well. To reintroduce excluded features, create a new object with a lower cutoff
min.features	Include cells where at least this many features are detected

Value

A Seurat object

Note

In previous versions (<3.0), this function also accepted a parameter to set the expression threshold for a ‘detected’ feature (gene). This functionality has been removed to simplify the initialization process/assumptions. If you would still like to impose this threshold for your particular dataset, simply filter the input expression matrix before calling this function.

Examples

## Not run: 
pbmc_raw <- read.table(
  file = system.file('extdata', 'pbmc_raw.txt', package = 'Seurat'),
  as.is = TRUE
)
pbmc_small <- CreateSeuratObject(counts = pbmc_raw)
pbmc_small

## End(Not run)

SeuratObject documentation built on May 29, 2024, 12:31 p.m.