Description
Enables easy loading of sparse data matrices provided by 10X genomics.
Usage
Read10X(
data.dir,
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`)
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