GenErode

GenErode processes whole-genome re-sequencing data from ancient, historical, and modern samples to produce comparable estimates of genomic erosion indices.

Key Features:

• Temporal Comparative Analysis: Simultaneously processes degraded ancient/historical DNA data alongside modern DNA data for direct comparison of genomic erosion patterns across time periods.
• Genomic Erosion Indices: Produces comparable estimates of multiple indices quantifying reduced genetic diversity, increased inbreeding, and accumulation of harmful mutations.
• Workflow Implementation: Written in Snakemake workflow language with Python3, using Conda and Singularity containers for reproducibility on high-performance compute clusters.

Scientific Applications:

• Conservation Genomics: Quantifies genomic consequences of population declines by comparing genome-wide data from pre-decline museum samples with modern samples in endangered species.
• Ancient DNA Analysis: Enables standardized processing and analysis of degraded DNA from historical or museum specimens alongside contemporary whole-genome re-sequencing data.

Methodology:

GenErode is written in Snakemake and Python3, uses Conda and Singularity containers, and processes whole-genome re-sequencing data using state-of-the-art bioinformatics tools.