PredCellTypes: Make predictions of cell types based on the single-cell...

In weilin-genomics/rSuperCT: A supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles

Description

Make predictions of cell types based on the single-cell RNA-seq digital expression profiles using a supervised classifier, SuperCT

Usage

PredCellTypes(
  object,
  species = "human",
  model = "38CellTypes",
  use.cells = NULL,
  results.dir = "."
)

Arguments

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

Value

Predicted cell identities saved in [e-mail][['pred_types']] or a data frame with cell identities

References

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

Examples

## Not run: 
myces <- PredCellTypes(myces, species = 'human', model = '38CellTypes', results.dir = '.')

## End(Not run)

weilin-genomics/rSuperCT documentation built on May 3, 2020, 1:42 p.m.