Regression analysis between ligand popularity and target gene predictive performance

get_slope_ligand_popularity: Performs regression analysis to investigate the trend between a particular classficiation evaluation metric and the popularity of the ligand.

Usage

get_slope_ligand_popularity(metric, performances)

Arguments

metric

The name of the performance metric of which the trend with the popularity of the ligand should be calculated.

performances

A data.frame in which the performance measures for target gene predictions of ligands are denoted together with the popularity of the ligand. (should contain at least following variables: ligand, ncitations and the metric of interest)

Value

A data.frame in which the regression coefficient estimate, p-value and corresponding R-squared value are shown for the regression analysis to investigate the trend between a particular classficiation evaluation metric and the popularity of the ligand.

Examples

if (FALSE) { # \dontrun{
library(dplyr)
weighted_networks <- construct_weighted_networks(lr_network, sig_network, gr_network, source_weights_df)
settings <- lapply(expression_settings_validation[1:10], convert_expression_settings_evaluation)
ligands <- extract_ligands_from_settings(settings)
ligand_target_matrix <- construct_ligand_target_matrix(weighted_networks, lr_network, ligands)
performances <- bind_rows(lapply(settings, evaluate_target_prediction, ligand_target_matrix))
# ncitations = get_ncitations_genes()
performances_ligand_popularity <- add_ligand_popularity_measures_to_perfs(performances, ncitations)
slopes_auroc <- get_slope_ligand_popularity("auroc", performances_ligand_popularity)
slopes_df <- performances_ligand_popularity %>%
  select(-setting, -ligand, -ncitations) %>%
  colnames() %>%
  lapply(., get_slope_ligand_popularity, performances_ligand_popularity) %>%
  bind_rows()
} # }