run_genetic_scenario

Run simulation with predefined biological scenarios

Tools to simulate genetic distance matrices, align and compare them via
multidimensional scaling (MDS) and Procrustes, and evaluate imputation with
the Bootstrapping Evaluation for Structural Missingness Imputation (BESMI)
framework. Methods align with Zhu et al. (2025) <doi:10.3389/fpls.2025.1543956>
and the associated software resource Zhu (2025) <doi:10.26188/28602953>.

Jiashuai Zhu

DataFusionGDM

Machine Learning for Integrating Partially Overlapped Genetic
Datasets

The University of Melbourne 

Agriculture Victoria 

run_genetic_scenario function

<dl><dt>scenario</dt>
<dd>Scenario name: 'default', 'island', 'stepping_stone', 'admixture', 'ancient_divergence', 'simple'</dd>
<dt>n_pops</dt>
<dd>Number of populations</dd>
<dt>output_file</dt>
<dd>Optional CSV path to write the distance matrix</dd>
<dt>seed</dt>
<dd>Optional seed forwarded to run_genetic_simulation()</dd>
<dt>verbose</dt>
<dd>Print diagnostic information</dd></dl>

Arguments

Run simulation with predefined biological scenarios — run_genetic_scenario

<dl>

<dt>scenario</dt>
<dd>Scenario name: 'default', 'island', 'stepping_stone', 'admixture', 'ancient_divergence', 'simple'</dd>


<dt>n_pops</dt>
<dd>Number of populations</dd>


<dt>output_file</dt>
<dd>Optional CSV path to write the distance matrix</dd>


<dt>seed</dt>
<dd>Optional seed forwarded to run_genetic_simulation()</dd>


<dt>verbose</dt>
<dd>Print diagnostic information</dd>

</dl>

run_genetic_scenario: Run simulation with predefined biological scenarios

Description

Usage

Value

Arguments