ZilionisLungData: Obtain the Zilionis lung cancer data

Description Usage Arguments Details Value Author(s) References Examples

View source: R/ZilionisLungData.R

Description

Obtain the human/mouse lung cancer single-cell RNA-seq data from Zilionis et al. (2019).

Usage

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ZilionisLungData(
  which = c("human", "mouse"),
  ensembl = FALSE,
  location = TRUE,
  filter = FALSE
)

Arguments

which

String specifying the species to get data for.

ensembl

Logical scalar indicating whether the output row names should contain Ensembl identifiers.

location

Logical scalar indicating whether genomic coordinates should be returned.

filter

Logical scalar indicating if the filtered subset should be returned.

Details

Column metadata is provided and contains information on the library, donor ID/animal ID, replicate and tissue.

If ensembl=TRUE, the gene symbols are converted to Ensembl IDs in the row names of the output object. Rows with missing Ensembl IDs are discarded, and only the first occurrence of duplicated IDs is retained.

If location=TRUE, the coordinates of the Ensembl gene models are stored in the rowRanges of the output. Note that this is only performed if ensembl=TRUE.

If filter=TRUE, only cells that have been used in the original analysis are returned. The cells used are specified in the Used column of the colData.

The reducedDim contains coordinates of SPRING representations. This may be filled with NAs for SPRING coordinates computed on a subset of cells (specified in colData).

All data are downloaded from ExperimentHub and cached for local re-use. Specific resources can be retrieved by searching for scRNAseq/zilionis-lung.

Value

A SingleCellExperiment object with a single matrix of read counts.

Author(s)

Jens Preussner

References

Zilionis R et al. (2019). Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species. Immunity 50(5), 1317-1334.

Examples

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sce.human <- ZilionisLungData()

sce.mouse <- ZilionisLungData("mouse")

drisso/scRNAseq documentation built on Feb. 16, 2021, 1:18 a.m.