calculate_metrics: Calculate Network Prediction Performance Metrics

In inferCSN: Inferring Cell-Specific Gene Regulatory Network

Calculate Network Prediction Performance Metrics

Description

Calculates comprehensive performance metrics for evaluating predicted network structures, including classification performance, precision-recall metrics, and network topology metrics.

Usage

calculate_metrics(
  network_table,
  ground_truth,
  metric_type = c("all", "auc", "auroc", "auprc", "precision", "recall", "f1",
    "accuracy", "si", "ji"),
  return_plot = FALSE,
  line_color = "#1563cc",
  line_width = 1
)

Arguments

network_table	A data frame of predicted network structure containing: regulator - Source nodes of the network edges target - Target nodes of the network edges weight - Edge weights representing prediction confidence
ground_truth	A data frame of ground truth network with the same format as network_table.
metric_type	The type of metric to return, default is all. This can take any of the following choices: all - Returns all available metrics with Performance Metrics plot auc - Returns both AUROC and AUPRC with their plots auroc - Area Under ROC Curve with plot auprc - Area Under Precision-Recall Curve with plot precision - Proportion of correct predictions among positive predictions recall - Proportion of actual positives correctly identified f1 - Harmonic mean of precision and recall accuracy - Overall classification accuracy si - Set Intersection, counting correctly predicted edges ji - Jaccard Index, measuring overlap between predicted and true networks
return_plot	Logical value, default is FALSE, whether to generate visualization plots
line_color	Color for plot lines, default is ⁠#1563cc⁠
line_width	Width for plot lines, default is 1

Value

A list containing:

• metrics - A data frame with requested metrics

• plot - A plot object if return_plot = TRUE (optional)

Examples

data("example_matrix")
data("example_ground_truth")
network_table <- inferCSN(example_matrix)
calculate_metrics(
  network_table,
  example_ground_truth,
  return_plot = TRUE
)
calculate_metrics(
  network_table,
  example_ground_truth,
  metric_type = "auroc"
)

inferCSN documentation built on April 13, 2025, 5:11 p.m.