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Mapache: a flexible pipeline to map ancient DNA.
Samuel Neuenschwander1,2, Diana I Cruz Dávalos1,3, Lucas Anchieri1,3
1Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.
Bioinformatics (Oxford, England)
|January 13, 2023
Summary
Mapache is a new bioinformatics pipeline for reproducible ancient and present-day DNA analysis. It efficiently maps, quantifies, and imputes DNA data, optimizing space for large datasets.
Area of Science:
- Bioinformatics
- Genomics
- Computational Biology
Background:
- Ancient DNA (aDNA) and present-day DNA analysis require robust and scalable computational tools.
- Existing pipelines may face challenges with large datasets, low-space consumption, and reproducibility.
Purpose of the Study:
- To introduce mapache, a flexible, robust, and scalable bioinformatics pipeline.
- To enable reproducible mapping, quantification, and imputation of ancient and present-day DNA data.
- To optimize low-space consumption for efficient processing of large genomic datasets.
Main Methods:
- Implementation using the Snakemake workflow manager.
- Optimization for low-space consumption.
- Designed for efficient (re)mapping of large datasets to reference genomes.
Main Results:
- Mapache provides a flexible, robust, and scalable solution for DNA data analysis.
- The pipeline is optimized for efficient processing of large reference panels and multiple samples.
- Reproducibility is ensured through its implementation in Snakemake.
Conclusions:
- Mapache offers an efficient and reproducible method for analyzing ancient and present-day DNA.
- The pipeline's design facilitates customization and integration with other Snakemake tools.
- Mapache is freely available, promoting wider adoption in the research community.
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