Perform batch-specific initial clustering.
Usage
initialClustering(
seu,
batch.var = "Batch",
cut.height = 0.4,
nfeatures = 2000,
additional.vars.to.regress = NULL,
dims = seq_len(14),
resolution = 0.6,
downsampling.size = 50,
verbose = FALSE
)Arguments
- seu
Seurat S4 object. Required.
- batch.var
Character. One of the column names of `seu@meta.data`. It is used to partition the Seurat object into smaller ones. Default: "Batch"
- cut.height
Numeric. Height used to cut hirerchical trees. Default: 0.4
- nfeatures
Number of high variance genes used. Default: 2000
- additional.vars.to.regress
Additional variables to regress out. Needs to among column names of `seu@meta.data`. Default: `NULL`
- dims
Number of dimension used for clustering. Passed to Seurat. Default: `1:14`
- resolution
Resolution for clustering. Passed to Seurat. Default: 0.6
- downsampling.size
Numeric. The number of cells representing each group. (Default: 40)
- verbose
Print the progress bar or not. Default: FALSE