Description Usage Arguments Value References Examples
Make predictions of cell types based on the single-cell RNA-seq digital expression profiles using a supervised classifier, SuperCT
1 2 3 4 5 6 7 | PredCellTypes(
object,
species = "human",
model = "38CellTypes",
use.cells = NULL,
results.dir = "."
)
|
object |
CellESet object or features x barcodes expression matrix |
species |
Either 'human' or 'mouse' for now |
model |
Choose a supported model. i.e 'CellTypes', 'CellStates' Please refer to https://github.com/weilin-genomics/SuperCT for more details. |
use.cells |
Character vector specify cells to make prediction for |
results.dir |
Specify directory to save downloaded required files for the prediction |
Predicted cell identities saved in object@meta.data[['pred_types']]
or a data frame with cell identities
Xie Peng and Gao Mingxuan (2019) SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles, https://doi.org/10.1093/nar/gkz116 Nucleic Acids Research
1 2 3 4 | ## Not run:
myces <- PredCellTypes(myces, species = 'human', model = '38CellTypes', results.dir = '.')
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.