Predict target from features

Usage

predictLOO(
  sce,
  target,
  group,
  interest_level,
  reference_level,
  types = NULL,
  channels = NULL,
  weights = NULL,
  n_threads = 1,
  assay_type = "tfmfeatures"
)

Arguments

sce: SingleCellExperiment object
target: Name of target variable for prediction
group: Grouping variable for cross-validation, e.g., patient
interest_level: Factor interest level in `target` variable
reference_level: Factor reference level in `target` variable
types: Vector of strings of feature types
channels: Vector of strings of feature channels
weights: Weights variable when features are aggregated
n_threads: Number of parallel threads for fitting of models
assay_type: A string specifying the assay

Value

tibble data frame

Examples

set.seed(23)
cell_file <- generate_data()
sce <- loadData(cell_file)
sce <- transformLogScale(sce)

sce$Drug <- as.factor(sce$Drug)
sce$Drug <- relevel(sce$Drug, ref = "D1")
types <- c("AreaShape", "Intensity", "Texture")

sce_single <- predictLOO(
    sce,
    target = "Drug", group = "Patient",
    interest_level = "D7", reference_level = "D1",
    types = types,
    n_threads = 1
)