Function to analyze benchmark results from attractor-based simulations

This function analyzes the results from benchmarking modeling methods on attractor-based simulation datasets. It computes the performance metrics: correlation coefficients for rate and random effect parameters, false positive rates (FPR), false discovery rates (FDR), and power for spatially variable gene (SVG) and functional spatial effect (FSE) parameters.

Usage

analyze_attractor_sim_benchmarks(results, sig_thresh = list(wisp = 0.05))

Arguments

results

The output of the run_attractor_sim_benchmarks function, either in its native form as a list, or converted into a data frame.

sig_thresh

A named list specifying the significance threshold for each modeling method when computing FPR, FDR, and power. Default is a list with a single entry for the "wisp" method set to 0.05. If a value is not specified for a method found in results, will use 0.05.

Value

A data frame summarizing the performance metrics for each modeling method.