dual_threshold_optimization 2.0.1

Dual Threshold Optimization compares two ranked lists of features (e.g. genes) to determine the rank threshold for each list that minimizes the hypergeometric p-value of the overlap of features. It then calculates a permutation based empirical p-value and an FDR. Details can be found [in this paper](https://doi.org/10.1101/gr.259655.119)
Documentation 
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//! # Core logic for the dual threshold optimization algorithm on two ranked lists.
//!
//! The main function is `optimize()`. The asymptotic complexity of the algorithm
//! is $O(n^2)$, where $n$ is the length of the threshold lists. See
//! `RankedFeatureList` for more information on the threshold lists.
pub mod compute_population_size;
pub mod optimize_main;
pub mod process_threshold_pairs;
pub mod results_objects;

pub use compute_population_size::compute_population_size;
pub use optimize_main::optimize;
pub use process_threshold_pairs::process_threshold_pairs;
pub use results_objects::{FeatureSets, OptimizationResult, OptimizationResultRecord};