Create a single-cell mRNA-seq experiment

create_sce_rnaseq(path, norm_method = "log_normalize")

Arguments

path

path to output matrices or R matrix object.

norm_method

Normalization method for counts. Normalized data is stored in logcounts. Set to NULL to skip normalization.

Value

SingleCellExperiment containing a sparseMatrix of counts

Examples

create_sce_rnaseq(scrunchy_data("mrna/"))
#> Loading sc-rnaseq matrix files: /home/travis/R/Library/scrunchy/extdata/mrna/
#> class: SingleCellExperiment #> dim: 9462 250 #> metadata(0): #> assays(2): counts logcounts #> rownames(9462): NOC2L HES4 ... AC004556.1 AC240274.1 #> rowData names(0): #> colnames(250): TGCGGGTGTAGAGTGC TGGTTCCCATCTATGG ... CTCGAAAAGTTCGATC #> TGACAACGTCGCATAT #> colData names(1): cell_id #> reducedDimNames(0): #> spikeNames(0): #> altExpNames(0):
# using pre-loaded matrix mat <- SingleCellExperiment::counts(fsce_small[["rnaseq"]]) create_sce_rnaseq(mat)
#> class: SingleCellExperiment #> dim: 9462 250 #> metadata(0): #> assays(2): counts logcounts #> rownames(9462): NOC2L HES4 ... AC004556.1 AC240274.1 #> rowData names(0): #> colnames(250): TGCGGGTGTAGAGTGC TGGTTCCCATCTATGG ... CTCGAAAAGTTCGATC #> TGACAACGTCGCATAT #> colData names(1): cell_id #> reducedDimNames(0): #> spikeNames(0): #> altExpNames(0):