Run Seurat analysis
runSeurat(object, ...) # S4 method for Seurat runSeurat( object, regressCellCycle = c("s-g2m-diff", "yes", "no"), varsToRegress = c("nCount_RNA", "mitoRatio"), dims = "auto", resolution = seq(from = 0.2, to = 1.2, by = 0.2), workers = "auto" ) # S4 method for SingleCellExperiment runSeurat(object, ...)
"s-g2m-diff": Calculate the difference between S and G2/M phases and use that to regress. See
CC.Differencemetric in Seurat vignette.
"yes": Regress out any effects of both S and G2/M phase variable. Refer to
"G2M.Score"metrics in Seurat vignette.
"no": Don't calculate cell-cycle scoring and don't regress.
Refer to the Seurat cell-cycle regression vignette for details.
NULL. Unwanted sources of variance to regress. Note that when
"no", then the corresponding cell-cycle variables are added automatically. Passes to Seurat::ScaleData internally.
integer. Dimensions of reduction to use as input for shared nearest neighbor (SNN) graph construction. When set to "auto" (default), the elbow point is calculated internally. See
plotPcElbow()for details. Passes to
numeric. Resolutions to calculate for clustering. Passes to
"uwot", changed to default in Seurat 3. Note that this sets
metric = "cosine"automatically.
"umap-learn", which requires reticulate. Note that this sets
metric = "correlation"automatically.
NULL. Disable parallelization with future by setting to