## code to prepare `marker_stats_1vAll` dataset goes here
## Use spatialLIBD to fetch the snRNA-seq dataset
sce_path_zip <- fetch_deconvo_data("sce")
## unzip and load the data
sce_path <- unzip(sce_path_zip, exdir = tempdir())
sce <- HDF5Array::loadHDF5SummarizedExperiment(
file.path(tempdir(), "sce_DLPFC_annotated")
)
## exclude Ambiguous cell type
sce <- sce[, sce$cellType_broad_hc != "Ambiguous"]
sce$cellType_broad_hc <- droplevels(sce$cellType_broad_hc)
## We're going to subset to the first 5k genes to save memory
sce <- sce[seq_len(5000), ]
## check the final dimensions of the dataset
dim(sce)
marker_stats_1vAll <- findMarkers_1vAll(
sce = sce, # sce is the SingleCellExperiment with our data
assay_name = "counts",
cellType_col = "cellType_broad_hc", # column in colData with cell type info
mod = "~BrNum" # Control for donor stored in "BrNum" with mod
)
# lobstr::obj_size(marker_stats_1vAll)
# 3.47 MB
usethis::use_data(marker_stats_1vAll, overwrite = TRUE)
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