Read10X: Load in data from 10X

In ibseq/scs-analysis: Tools for Single Cell Genomics

Description

Enables easy loading of sparse data matrices provided by 10X genomics.

Usage

Read10X(
  data.dir = NULL,
  gene.column = 2,
  cell.column = 1,
  unique.features = TRUE,
  strip.suffix = FALSE
)

Arguments

data.dir	Directory containing the matrix.mtx, genes.tsv (or features.tsv), and barcodes.tsv files provided by 10X. A vector or named vector can be given in order to load several data directories. If a named vector is given, the cell barcode names will be prefixed with the name.
gene.column	Specify which column of genes.tsv or features.tsv to use for gene names; default is 2
cell.column	Specify which column of barcodes.tsv to use for cell names; default is 1
unique.features	Make feature names unique (default TRUE)
strip.suffix	Remove trailing "-1" if present in all cell barcodes.

Value

If features.csv indicates the data has multiple data types, a list containing a sparse matrix of the data from each type will be returned. Otherwise a sparse matrix containing the expression data will be returned.

Examples

## Not run: 
# For output from CellRanger < 3.0
data_dir <- 'path/to/data/directory'
list.files(data_dir) # Should show barcodes.tsv, genes.tsv, and matrix.mtx
expression_matrix <- Read10X(data.dir = data_dir)
seurat_object = CreateSeuratObject(counts = expression_matrix)

# For output from CellRanger >= 3.0 with multiple data types
data_dir <- 'path/to/data/directory'
list.files(data_dir) # Should show barcodes.tsv.gz, features.tsv.gz, and matrix.mtx.gz
data <- Read10X(data.dir = data_dir)
seurat_object = CreateSeuratObject(counts = data$`Gene Expression`)
seurat_object[['Protein']] = CreateAssayObject(counts = data$`Antibody Capture`)

## End(Not run)

ibseq/scs-analysis documentation built on Feb. 27, 2021, 12:35 a.m.