Creates a Seurat object containing only a subset of the cells in the original object. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on.
SubsetData(object, ...)# S3 method for Assay
SubsetData(
object,
cells = NULL,
subset.name = NULL,
low.threshold = -Inf,
high.threshold = Inf,
accept.value = NULL,
...
)
# S3 method for Seurat
SubsetData(
object,
assay = NULL,
cells = NULL,
subset.name = NULL,
ident.use = NULL,
ident.remove = NULL,
low.threshold = -Inf,
high.threshold = Inf,
accept.value = NULL,
max.cells.per.ident = Inf,
random.seed = 1,
...
)
An object
Arguments passed to other methods
A vector of cell names to use as a subset. If NULL (default), then this list will be computed based on the next three arguments. Otherwise, will return an object consissting only of these cells
Parameter to subset on. Eg, the name of a gene, PC_1, a column name in object@meta.data, etc. Any argument that can be retreived using FetchData
Low cutoff for the parameter (default is -Inf)
High cutoff for the parameter (default is Inf)
Returns cells with the subset name equal to this value
Assay to subset on
Create a cell subset based on the provided identity classes
Subtract out cells from these identity classes (used for filtration)
Can be used to downsample the data to a certain max per cell ident. Default is INF.
Random seed for downsampling
Returns a Seurat object containing only the relevant subset of cells
# NOT RUN {
pbmc1 <- SubsetData(object = pbmc_small, cells = colnames(x = pbmc_small)[1:40])
pbmc1
# }
# NOT RUN {
# }
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