Read10xData: Create Seurat Object from sparse data matrices provided by...
In Theob0t/scEasyPip: Automated Seurat Pipeline for scRNA-seq analysis

This function create a Seurat object from a 10x output directory by loading a matrix (matrix.mtx.gz), a barcode file (barcodes.tsv.gz) and a feature file (features.tsv.gz) from the current directory.

Read10xData(
  data.dir,
  output.dir = NULL,
  min.cells = 3,
  min.features = 200,
  mt.pattern = "^mt-",
  project.name = "SeuratProject",
  ...
)

`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.
`output.dir`	Path to the destination folder of saved files
`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.
`mt.pattern`	Regex pattern of the mitochondrial genes ('^MT-' or '^mt-')
`project.name`	Name of the project/object used for titles in plots
`...`	Arguments passed to `as.sparse`