Human pancreatic islet cell datasets produced across four technologies,
SMART-Seq2 (E-MTAB-5061), CelSeq (GSE81076), CelSeq2 (GSE85241), and Fluidigm C1 (GSE86469),
from SeuratData package.
For each data set in panc8, 200 cells were downsampled to form the panc8_sub dataset.
Examples
if (interactive()) {
data(pancreas_sub)
archive <- tempfile(fileext = ".tar.gz")
utils::download.file(
"https://seurat.nygenome.org/src/contrib/panc8.SeuratData_3.0.2.tar.gz",
archive,
mode = "wb"
)
exdir <- tempfile()
utils::untar(archive, files = "panc8.SeuratData/data/panc8.rda", exdir = exdir)
load(file.path(exdir, "panc8.SeuratData", "data", "panc8.rda"))
panc8 <- SeuratObject::UpdateSeuratObject(panc8)
set.seed(98)
cells_sub <- unlist(
lapply(
split(colnames(panc8), panc8$dataset),
function(x) sample(x, size = 200)
)
)
panc8_sub <- subset(panc8, cells = cells_sub)
counts <- GetAssayData5(
panc8_sub,
layer = "counts"
)
panc8_sub <- SeuratObject::CreateSeuratObject(
counts = counts,
meta.data = panc8_sub@meta.data
)
panc8_sub <- panc8_sub[Matrix::rowSums(counts) > 0, ]
panc8_sub <- panc8_sub[toupper(
rownames(panc8_sub)
) %in% toupper(
rownames(pancreas_sub)
), ]
panc8_sub$celltype <- gsub("_", "-", panc8_sub$celltype)
panc8_sub$celltype <- gsub(" ", "-", panc8_sub$celltype)
usethis::use_data(
panc8_sub,
compress = "xz",
overwrite = TRUE
)
}