R/DarmanisBrainData.R

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

#' Obtain the Darmanis brain data
#'
#' Obtain the human brain single-cell RNA-seq dataset from Darmanis et al. (2015).
#'
#' @param ensembl Logical scalar indicating whether the output row names should contain Ensembl identifiers.
#' @param location Logical scalar indicating whether genomic coordinates should be returned.
#' @param remove.htseq Logical scalar indicating whether HT-seq alignment statistics should be removed.
#' @param legacy Logical scalar indicating whether to pull data from ExperimentHub.
#' By default, we use data from the gypsum backend.
#' 
#' @details
#' Column metadata is scraped from GEO and includes patient information, tissue of origin and likely cell type. 
#'
#' If \code{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 \code{location=TRUE}, the coordinates of the Ensembl gene models are stored in the \code{\link{rowRanges}} of the output.
#' This is only performed when \code{ensembl=TRUE}.
#'
#' All data are downloaded from ExperimentHub and cached for local re-use.
#' Specific resources can be retrieved by searching for \code{scRNAseq/darmanis-brain}.
#'
#' @return A \linkS4class{SingleCellExperiment} object with a single matrix of UMI counts.
#'
#' @author Aaron Lun
#'
#' @references
#' Darmanis S et al. (2015). 
#' A survey of human brain transcriptome diversity at the single cell level. 
#' \emph{Proc Natl Acad Sci USA} 112, 7285-90.
#'
#' @examples
#' sce <- DarmanisBrainData()
#' 
#' @export
DarmanisBrainData <- function(ensembl=FALSE, location=TRUE, remove.htseq=TRUE, legacy=FALSE) {
    if (!legacy && remove.htseq) {
        sce <- fetchDataset("darmanis-brain-2015", "2023-12-21", realize.assays=TRUE)
    } else {
        version <- "2.6.0"
        sce <- .create_sce(file.path("darmanis-brain", version), has.rowdata=FALSE)

        if (remove.htseq) {
            to.drop <- c("no_feature", "ambiguous", "alignment_not_unique")
            sce <- sce[!rownames(sce) %in% to.drop,]
        }
    }

    .convert_to_ensembl(sce, 
        symbols=rownames(sce), 
        species="Hs",
        ensembl=ensembl,
        location=location)
}