Internal function to compute y_hat on a subset of the features

Usage

compute_y_hat(
  feature_name,
  sce_feature,
  starts,
  target,
  group,
  interest_level,
  reference_level,
  weights,
  n_threads,
  assay_type
)

Arguments

feature_name: String with feature name
sce_feature: SingleCellExperiment
starts: Starting string
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
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