read10XResults: Load in data from 10X experiment

In dynverse/scaterlegacy: Single-cell analysis toolkit for gene expression data in R

Description

Creates a full or sparse matrix from a sparse data matrix provided by 10X genomics.

Usage

read10XResults(data_dir = NULL, min_total_cell_counts = 1000L,
  min_mean_gene_counts = NULL, expand = TRUE, logExprsOffset = 1)

Arguments

data_dir	Directory containing the matrix.mtx, genes.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.
min_total_cell_counts	integer(1) threshold such that cells (barcodes) with total counts below the threshold are filtered out
min_mean_gene_counts	numeric(1) threshold such that genes with mean counts below the threshold are filtered out.
expand	logical(1), should the sparse count matrix be expanded into an SCESet object with dense matrices for expression data (default), or should the sparse count matrix be returned?
logExprsOffset	numeric(1) offset value to apply when computing expression values as log2(cpm + offset) for the SCESet. Ignored if expand = FALSE.

Details

This function was developed from the Read10X function from the Seurat package.

Value

If expand is TRUE, returns an SCESet object with counts data and log2(cpm + offset) as expression data; else returns a sparse matrix with rows and columns labeled.

Examples

## Not run: 
sce10x <- read10XResults("path/to/data/directory")
count_matrix_10x <- read10XResults("path/to/data/directory", expand = FALSE)

## End(Not run)

dynverse/scaterlegacy documentation built on Feb. 17, 2020, 5:07 a.m.