Compare performance of multiple trained models

Computes and summarizes performance metrics across multiple drug models. Returns performance in cross-validation, bulk test, pseudo-bulk, and scRNA datasets.

Usage

compare_performance(model_list, threshold = 0.3, verbose = TRUE)

Arguments

model_list

A named list of trained model objects from train_models().

threshold

Numeric. Minimum correlation threshold for "passing" models. Default = 0.3.

verbose

Logical. Whether to print summary statistics. Default = TRUE.

Value

A list containing:

perf_cv

Cross-validation performance (|correlation| = sqrt(R²); p-value not available) for each drug

perf_bulk

Bulk test set performance for each drug

perf_pseudo_bulk

Pseudo-bulk performance for each drug

perf_scRNA

Single-cell RNA performance for each drug

summary

Summary statistics of models passing threshold

Examples

if (FALSE) { # \dontrun{
  models <- train_models(drug_list = c("abemaciclib", "erlotinib"))
  perf <- compare_performance(models)
} # }