Train a prediction model — trainModel • scPred

Trains a prediction model from an scPred object stored in a Seurat object

trainModel(
  object,
  model = "svmRadial",
  preProcess = c("center", "scale"),
  resampleMethod = "cv",
  number = 5,
  seed = 66,
  tuneLength = 3,
  metric = c("ROC", "PR", "Accuracy", "Kappa"),
  returnData = FALSE,
  savePredictions = "final",
  allowParallel = FALSE,
  reclassify = NULL
)

Arguments

object	An `Seurat` or `scPred` object after running `getFeatureSpace`
model	Classification model supported via `caret` package. A list of all models can be found here:
preProcess	A string vector that defines a pre-processing of the predictor data. Current possibilities are "BoxCox", "YeoJohnson", "expoTrans", "center", "scale", "range", "knnImpute", "bagImpute", "medianImpute", "pca", "ica" and "spatialSign". The default is "center" and "scale. See preProcess and trainControl on the procedures and how to adjust them https://topepo.github.io/caret/available-models.html Default: support vector machine with radial kernel
resampleMethod	Resample model used in `trainControl` function from `caret`. Default: K-fold cross validation
number	Number of iterations for resample method. See `trainControl` function
seed	Numeric seed for resample method. Fixed to ensure reproducibility
tuneLength	An integer denoting the amount of granularity in the tuning parameter grid. By default, this argument is the number of levels for each tuning parameters that should be generated by train. See `?caret::train` documentation
metric	Performance metric to be used to select best model: `ROC` (area under the ROC curve), `PR` (area under the precision-recall curve), `Accuracy`, and `Kappa`
returnData	If `TRUE`, training data is returned within `scPred` object.
savePredictions	Specifies the set of hold-out predictions for each resample that should be returned. Values can be either "all", "final", or "none".
allowParallel	Allow parallel processing for resampling?
reclassify	Cell types to reclassify using a different model

Value

A list of train objects for each cell class (e.g. cell type). See train function for details.

Author

Jose Alquicira Hernandez