Artificial Intelligence for Unified Analysis of Historical and Landscape Influences on Genetic Diversity

Overview

This repository contains scripts and resources related to the paper titled "Artificial Intelligence Enables Unified Analysis of Historical and Landscape Influences on Genetic Diversity." The goal of this project is to provide a unified platform for analyzing the influences of historical and landscape factors on genetic diversity, leveraging artificial intelligence techniques.

Getting Started

To initiate the analysis follow these steps:

1. Locality and Demographic Information Extraction:

   • Run Species_information_L_troglodytes.R to extract information about localities and demographic history for the species Leptodactylus troglodytes.
   • Run Species_information_R_granulosa.R to extract information about localities and demographic history for the species Rhinella granulosa.

2. Genomic Image Creation:

   • Execute Observed_image_L_troglodytes.R to generate images from genomic information for the species Leptodactylus troglodytes.
   • Execute Observed_image_R_granulosa.R to generate images from genomic information for the species Rhinella granulosa.

3. Simulated Dataset Generation and HPC Submission Scripts:

   • Utilize Main_script_script_L_troglodytes.R to generate scripts for running simulated datasets and creating PBS scripts for HPC submission for the species Leptodactylus troglodytes.
   • Utilize Main_script_script_R_granulosa.R for the same purpose but for the species Rhinella granulosa.

4. Convolutional Neural Network (CNN) Model Execution:

   • Run CNN_script_L_troglodytes.py to execute the CNN model for the species Leptodactylus troglodytes.
   • Run CNN_script_R_granulosa.py to execute the CNN model for the species Rhinella granulosa.

Make sure to review and customize the input parameters within each script according to your specific requirements. Additionally, ensure that all dependencies are installed before running the scripts by using the provided requirements files or installing them manually.