ybyra: Y-chromosome haplogroup calling using a tree-based scoring method

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Abstract

Summary We present ybyra , a Snakemake workflow for automated Y-chromosome haplogroup assignment using a tree-based scoring method with robust and transparent heuristics. The pipeline supports both human reference genome builds 37 and 38, makes use of three different well-curated Y-SNP tree topologies and features an optional ancient DNA damage filter to accommodate low-coverage degraded samples. ybyra produces reproducible, scalable haplogroup calls with detailed scoring outputs to facilitate quality assessment and reporting. We further showcase its versatility by applying it to horse Y-chromosome data, highlighting its applicability beyond humans. Availability ybyra is published under the MIT license and freely available at github.com/tpinotti/ybyra .
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Acknowledgements

The authors thank J. Víctor Moreno-Mayar for helpful suggestions, and the ISOGG, YFull and FamilyTree DNA teams for their work curating the human Y -SNP tree and making it publicly available for the research community. The Lundbeck Foundation GeoGenetics Centre is supported by the Lundbeck Foundation (grant nos. R302-2018-2155, R155-2013-16338), the Novo Nordisk Foundation (grant no. NNF18SA0035006), the Wellcome Trust (grant no. UNS69906), Carlsberg Foundation (grant no . CF18 -0024), the Danish National Research Foundation (grant nos. DNRF94, DNRF174), the University of Copenhagen (KU2016 programme) . All authors were supported by the Novo Nordisk Foundation and Wellcome Trust (AEGIS project) and the Danish National Research Foundation Center for Ancient Environmental Genomics (CAEG). Competing interests: The authors declare no competing interests. .CC-BY-NC 4.0 International licenseavailable under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprintthis version posted November 20, 2025. ; https://doi.org/10.1101/2025.11.20.689455doi: bioRxiv preprint

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