# sedimix: a workflow for the analysis of hominin nuclear DNA sequences from sediments

## TL;DR

The paper introduces sedimix, an open-source workflow for analyzing ancient hominin DNA from sediments, improving reproducibility and accuracy in sediment DNA studies.

## Contribution

The novel contribution is the development of sedimix, a Snakemake-based workflow for reliable and reproducible analysis of hominin sediment DNA.

## Key findings

- Sedimix accurately identifies hominin sequences and generates summary statistics for reliability assessment.
- Validation using simulations and published data shows sedimix yields accurate and reliable inferences.
- Sedimix improves reproducibility and adaptability in sediment DNA analysis across studies.

## Abstract

Sediment DNA—the recovery of genetic material from archaeological sediments—is an exciting new frontier in ancient DNA research, offering the potential to study individuals at a given archaeological site without destructive sampling. In recent years, several studies have demonstrated the promise of this approach by extracting hominin DNA from prehistoric sediments, including those dating back to the Middle or Late Pleistocene. However, a lack of open-source workflows for analysis of hominin sediment DNA samples poses a challenge for data processing and reproducibility of findings across studies. Here, we introduce a snakemake workflow, sedimix, for processing genomic sequences from archaeological sediment DNA samples to identify hominin sequences and generate relevant summary statistics to assess the reliability of the pipeline. By performing simulations and comparing our results to two published studies with human DNA from ∼25,000 years ago (including shotgun data from a sediment sample and capture data from touch DNA recovered from a deer tooth pendant) we demonstrate that sedimix yields accurate and reliable inferences. sedimix offers a reliable and adaptable framework to aid in the analysis of sediment DNA datasets and improve reproducibility across studies.

sedimix is available as an open-source software with the associated code, example data, and user manual with installation instructions available at https://github.com/jierui-cell/sedimix. A permanent archived version of this release is available via Zenodo: https://doi.org/10.5281/zenodo.17244854.