read10xCounts {DropletUtils}R Documentation

Load in data from 10x experiment

Description

Creates a SingleCellExperiment from the CellRanger output directories for 10X Genomics data.

Usage

read10xCounts(samples, col.names=FALSE, type=c("auto", "sparse", "HDF5"), 
    group=NULL) 

Arguments

samples

A character vector containing one or more directory names, each corresponding to a 10X sample. Each directory should contain the "matrix.mtx", "genes.tsv" and "barcodes.tsv" files generated by CellRanger.

Alternatively, strings may contain a path to a HDF5 file in the sparse matrix format generated by 10X. These can be mixed with directory names when type="auto".

col.names

A logical scalar indicating whether the columns of the output object should be named with the cell barcodes.

type

String specifying the type of 10x format to read data from.

group

String specifying the group name if type="HDF5".

Details

This function was originally developed from the Read10X function from the Seurat package. It was then taken from the read10xResults implementation in the scater package.

If type="auto", the format is automatically detected for each samples based on whether it ends with ".h5". If so, type is set to "HDF5"; otherwise it is set to "sparse".

Matrices are combined by column if multiple samples were specified. This will throw an error if the gene information is not consistent across samples.

If col.names=TRUE and length(sample)==1, each column is named by the cell barcode. For multiple samples, the columns are unnamed to avoid problems with non-unique barcodes across samples.

Note that user-level manipulation of sparse matrices requires loading of the Matrix package. Otherwise, calculation of rowSums, colSums, etc. will result in errors.

Value

A SingleCellExperiment object containing count data for each gene (row) and cell (column) across all samples.

Author(s)

Davis McCarthy, with modifications from Aaron Lun

References

Zheng GX, Terry JM, Belgrader P, and others (2017). Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049.

10X Genomics (2017). Gene-Barcode Matrices. https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/output/matrices

10X Genomics (2018). HDF5 Gene-Barcode Matrix Format. https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/advanced/h5_matrices

See Also

write10xCounts

Examples

# Mocking up some 10X genomics output.
example(write10xCounts)

# Reading it in.
sce10x <- read10xCounts(tmpdir)

# Column names are dropped with multiple 'samples'.
sce10x2 <- read10xCounts(c(tmpdir, tmpdir))

[Package DropletUtils version 1.2.2 Index]