data-raw/pbmc_v2.R

In steinbaugh/Chromium: 10X Genomics Chromium

## 10X Chromium Cell Ranger v2 example output.
##
## 4k PBMCs from a healthy donor.
##
## Updated 2022-06-07.
##
## https://support.10xgenomics.com/single-cell-gene-expression/datasets/
## 2.1.0/pbmc4k

## nolint start
suppressPackageStartupMessages({
    library(devtools)
    library(usethis)
    library(AcidBase)
    library(AcidExperiment)
    library(pipette)
})
## nolint end

load_all()
datasetName <- "pbmc_v2"
limit <- structure(2e6L, class = "object_size")

## Complete dataset ============================================================
dir <- initDir(datasetName)
if (dir.exists(dir)) {
    unlink2(dir)
}
sampleDir <- initDir(file.path(dir, "pbmc"))
outsDir <- initDir(file.path(sampleDir, "outs"))
counterDir <- initDir(file.path(sampleDir, "SC_RNA_COUNTER_CS"))
file.create(file.path(counterDir, "empty"))
urlStem <- pasteUrl(
    "cf.10xgenomics.com",
    "samples",
    "cell-exp",
    "2.1.0",
    "pbmc4k",
    protocol = "http"
)
urls <- paste(
    urlStem,
    paste0(
        "pbmc4k_",
        c(
            ## > "filtered_gene_bc_matrices_h5.h5", # 403 (2019-08-22)
            "filtered_gene_bc_matrices.tar.gz",
            "metrics_summary.csv",
            "molecule_info.h5",
            "raw_gene_bc_matrices_h5.h5",
            "raw_gene_bc_matrices.tar.gz"
        )
    ),
    sep = "/"
)
files <- vapply(
    X = urls,
    pkg = .pkgName,
    FUN = cacheUrl,
    FUN.VALUE = character(1L),
    USE.NAMES = FALSE
)
names(files) <- gsub(
    pattern = "^pbmc4k_",
    replacement = "",
    x = basename(urls)
)
tarfile <- grep(
    pattern = "filtered_gene_bc_matrices\\.tar\\.gz$",
    x = files,
    value = TRUE
)
untar(
    tarfile = files[["filtered_gene_bc_matrices.tar.gz"]],
    exdir = outsDir
)
file.copy(
    from = files[["metrics_summary.csv"]],
    to = file.path(outsDir, "metrics_summary.csv")
)
file.copy(
    from = files[["molecule_info.h5"]],
    to = file.path(outsDir, "molecule_info.h5")
)
gffFile <- cacheUrl(
    url = pasteUrl(
        "ftp.ensembl.org",
        "pub",
        "release-84",
        "gtf",
        "homo_sapiens",
        "Homo_sapiens.GRCh38.84.gtf.gz",
        protocol = "ftp"
    ),
    pkg = .pkgName
)
object <- CellRanger(
    dir = dir,
    organism = "Homo sapiens",
    gffFile = gffFile
)
assignAndSaveData(
    name = datasetName,
    object = object,
    dir = getwd()
)

## Example object ==============================================================
counts <- counts(object)
topGenes <-
    counts |>
    Matrix::rowSums() |>
    sort(decreasing = TRUE) |>
    head(n = 500L)
genes <- sort(names(topGenes))
topCells <-
    counts |>
    Matrix::colSums() |>
    sort(decreasing = TRUE) |>
    head(n = 100L)
cells <- sort(names(topCells))
object <- object[genes, cells]
stopifnot(
    object.size(object) < limit,
    validObject(object)
)
pbmc_v2 <- object # nolint
use_data(pbmc_v2, compress = "xz", overwrite = TRUE)

## Example Cell Ranger v2 output ===============================================
inputDir <- dir
inputSampleDir <- sampleDir
inputOutsDir <- outsDir
inputMatrixDir <- file.path(
    inputOutsDir,
    "filtered_gene_bc_matrices",
    "GRCh38"
)
outputDir <- file.path(
    "..",
    "inst",
    "extdata",
    "cellranger_v2"
)
if (dir.exists(outputDir)) {
    unlink2(outputDir)
}
outputSampleDir <- initDir(file.path(outputDir, "pbmc"))
outputOutsDir <- initDir(file.path(outputSampleDir, "outs"))
outputCounterDir <- initDir(file.path(outputSampleDir, "SC_RNA_COUNTER_CS"))
file.create(file.path(outputCounterDir, "empty"))
outputMatrixDir <- initDir(file.path(
    outputOutsDir,
    "filtered_gene_bc_matrices",
    "GRCh38"
))
file.copy(
    from = file.path(outsDir, "metrics_summary.csv"),
    to = file.path(outputOutsDir, "metrics_summary.csv")
)
counts <- import(file.path(inputMatrixDir, "matrix.mtx"))
counts <- counts[seq_len(100L), seq_len(100L)]
export(
    object = counts,
    con = file.path(outputMatrixDir, "matrix.mtx")
)
genes <- import(
    con = file.path(inputMatrixDir, "genes.tsv"),
    colnames = FALSE,
    nMax = 100L
)
stopifnot(identical(nrow(genes), 100L))
export(
    object = genes,
    con = file.path(outputMatrixDir, "genes.tsv"),
    colnames = FALSE
)
barcodes <- import(
    con = file.path(inputMatrixDir, "barcodes.tsv"),
    nMax = 100L
)
stopifnot(identical(nrow(barcodes), 100L))
export(
    object = barcodes,
    con = file.path(outputMatrixDir, "barcodes.tsv"),
    colnames = FALSE
)