CreateSeuratObject: Create a 'Seurat' object

Description Usage Arguments Value Note Examples

View source: R/generics.R

Description

Create a Seurat object from raw data

Usage

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

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

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

Arguments

counts

Either a matrix-like object with unnormalized data with cells as columns and features as rows or an Assay-derived object

project

Project name for the Seurat 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.

...

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

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pbmc_raw <- read.table(
  file = system.file('extdata', 'pbmc_raw.txt', package = 'Seurat'),
  as.is = TRUE
)
pbmc_small <- CreateSeuratObject(counts = pbmc_raw)
pbmc_small

Seurat documentation built on Jan. 13, 2021, 7:11 p.m.