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Human pancreatic islet cell datasets produced across four technologies, CelSeq (GSE81076) CelSeq2 (GSE85241), Fluidigm C1 (GSE86469), and SMART-Seq2 (E-MTAB-5061) from SeuratData package. For each data set in `panc8`, 200 cells were downsampled to form the panc8_sub dataset.

Format

A Seurat object.

Examples

if (FALSE) { # \dontrun{
if (interactive()) {
  data(pancreas_sub)
  if (!require("SeuratData", quietly = TRUE)) {
    pak::pak("satijalab/seurat-data")
  }
  library(SeuratData)
  library(Seurat)
  suppressWarnings(InstallData("panc8"))
  data("panc8")
  panc8 <- UpdateSeuratObject(panc8)
  set.seed(42)
  cells_sub <- unlist(
    lapply(
      split(colnames(panc8), panc8$dataset),
      function(x) sample(x, size = 200)
    )
  )
  panc8_sub <- subset(panc8, cells = cells_sub)
  counts <- GetAssayData5(
    panc8_sub,
    slot = "counts"
  )
  panc8_sub <- CreateSeuratObject(
    counts = counts,
    meta.data = panc8_sub@meta.data
  )
  panc8_sub <- panc8_sub[Matrix::rowSums(counts) > 0, ]
  panc8_sub <- panc8_sub[toupper(
    rownames(panc8_sub)
  ) %in% toupper(
    rownames(pancreas_sub)
  ), ]
  panc8_sub$celltype <- gsub("_", "-", panc8_sub$celltype)
  panc8_sub$celltype <- gsub(" ", "-", panc8_sub$celltype)
  panc8_sub <- NormalizeData(panc8_sub)
  panc8_sub <- FindVariableFeatures(panc8_sub)
  panc8_sub <- ScaleData(panc8_sub)
  panc8_sub <- RunPCA(panc8_sub)
  panc8_sub <- RunUMAP(panc8_sub, dims = 1:20)
  usethis::use_data(
    panc8_sub,
    compress = "xz",
    overwrite = TRUE
  )
}
} # }