PredictCellCycle
This function predicts the cell cycle state for each cell in the object using the ccAFv2 cell cycle classifier. The possible cell cycle states that ccAFv2 can predict are: Neural G0, G1, G1/other, Late G1, S, S/G2, G2/M, and M/Early G1.
PredictCellCycle(
seurat_obj,
threshold = 0.5,
include_g0 = FALSE,
do_sctransform = TRUE,
assay = "SCT",
species = "human",
gene_id = "ensembl",
spatial = FALSE
)
Arguments
| Arguments | Range of Values | Description |
|---|---|---|
| seurat_obj | NA | a seurat object must be supplied to classify, no default |
| threshold | Numeric (0 to 1) | the value used to threshold the likelihoods, default is 0.5 |
| include_g0 | TRUE or FALSE | whether to provide Neural G0 calls, or collapse G1 and Neural G0 into G0/G1, default is FALSE |
| do_sctransform | TRUE or FALSE | whether to do SCTransform before classifying, default is TRUE |
| assay | ‘SCT’, ‘RNA’, etc. | which seurat_obj assay to use for classification, helpful if data is pre-normalized, default is ‘SCT’ |
| species | ‘human’ or ‘mouse’, | from which species did the samples originate, default is ‘human’ |
| gene_id | ‘ensembl’ or ‘symbol’, | what type of gene ID is used, default is ‘ensembl’ |
| spatial | TRUE or FALSE | whether the data is spatial, default is FALSE |
Value
Returns the input Seurat object, with:
-
Cell cycle prediction probabilities added to the metadata (one column per class).
-
A ‘ccAFv2’ column in metadata containing the assigned cell cycle state per cell.
Example
# Run classifier and add predictions to Seurat metadata
seurat_obj = PredictCellCycle(seurat_obj)