polishDataset: Polish dataset for saving

In LTLA/scRNAseq: Collection of Public Single-Cell RNA-Seq Datasets

Polish dataset for saving

Description

Prepare a SummarizedExperiment or SingleCellExperiment to be saved with saveDataset. This performs some minor changes to improve storage efficiency.

Usage

polishDataset(
  x,
  strip.inner.names = TRUE,
  reformat.assay.by.density = 0.3,
  attempt.integer.conversion = TRUE,
  remove.altexp.coldata = TRUE,
  forbid.nested.altexp = TRUE
)

Arguments

x	A SummarizedExperiment or one of its subclasses.
strip.inner.names	Logical scalar indicating whether to strip redundant names from internal objects, e.g., dimnames of the assays, row names of reduced dimensions, column names of alternative experiments. This saves some space in the on-disk representation.
reformat.assay.by.density	Numeric scalar indicating whether to optimize assay formats based on the density of non-zero values. Assays with densities above this number are converted to ordinary dense arrays (if they are not already), while those with lower densities are converted to sparse matrices. This can be disabled by setting it to NULL.
attempt.integer.conversion	Logical scalar indicating whether to convert double-precision assays containing integer values to actually have the integer type. This can improve efficiency of downstream applications by avoiding the need to operate in double precision.
remove.altexp.coldata	Logical scalar indicating whether column data for alternative experiments should be removed. This defaults to TRUE as the alternative experiment column data is usually redundant with that of the main experiment.
forbid.nested.altexp	Logical scalar indicating whether nested alternative experiments (i.e., alternative experiments of alternative experiments) should be forbidden. This defaults to TRUE as nested alternative experiments are usually the result of some mistake in altExp preparation.

Value

A modified copy of x.

Author(s)

Aaron Lun

Examples

mat <- matrix(rpois(1000, lambda=0.2), 100, 10) * 1.0
rownames(mat) <- sprintf("GENE_%i", seq_len(nrow(mat)))
colnames(mat) <- head(LETTERS, 10)

library(SingleCellExperiment)
sce <- SingleCellExperiment(list(counts=mat))
str(assay(sce, withDimnames=FALSE))

polished <- polishDataset(sce)
str(assay(polished, withDimnames=FALSE))

LTLA/scRNAseq documentation built on April 24, 2024, 5:58 p.m.