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Read paired 10x RNA and ATAC counts

Source: R/ReadMultiomeData.R
ReadMultiomeData.Rd

Import both measured modalities from one local 10x ARC count matrix without dropping cells, normalizing counts, or inferring RNA from ATAC.

Usage

ReadMultiomeData(
  object,
  metadata = NULL,
  cell.names = NULL,
  sample = NULL,
  genome = NULL,
  annotation = NULL,
  fragments = NULL,
  fragment.cells = NULL,
  assay = "peaks",
  rna.assay = "RNA",
  project = "Multiome",
  verbose = TRUE
)

Arguments

object

Path to one 10x ARC H5 file or one matrix directory containing matrix.mtx.gz, features.tsv.gz and barcodes.tsv.gz. The input must contain exactly the Gene Expression and Peaks modalities. H5 input requires at least two features per modality and two cells because the Seurat H5 reader otherwise drops matrix dimensions.

metadata, cell.names, sample, genome, annotation, fragments, fragment.cells, project, verbose

Passed to ReadATACData(). Metadata and sample vectors use original barcodes; fragment mappings use final cell names.

assay

Name of the chromatin assay, default "peaks".

rna.assay

Name of the measured RNA assay, default "RNA".

Value

A Seurat object with a ChromatinAssay and a measured RNA Assay, both containing raw counts for the same ordered cells. The active assay is assay. Provenance is stored in Misc(object, "scop_multiome_input") and in the ATAC import receipt. Assay initialization also copies raw counts to the data layer; this is not normalized expression.

Details

Gene IDs, rather than potentially duplicated gene symbols, identify RNA features. Both modalities must contain the same unique barcodes. Their counts are explicitly aligned to the ATAC barcode order. Peak coordinates in 10x files are 0-based half-open and are converted to 1-based closed coordinates. No barcode suffixes are removed and no absent modality is zero-filled. H5 input requires the optional hdf5r package. Fragment files remain external references, as described in ReadATACData().

See also

ReadATACData(), CheckATACData()

Examples

if (FALSE) { # \dontrun{
multiome <- ReadMultiomeData("filtered_feature_bc_matrix.h5", genome = "hg38")
} # }