BADGER: evaluating the performance of ancient DNA genetic relatedness estimation methods using high-fidelity pedigree simulations

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BADGER: evaluating the performance of ancient DNA genetic relatedness estimation methods using high-fidelity pedigree simulations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article BADGER: evaluating the performance of ancient DNA genetic relatedness estimation methods using high-fidelity pedigree simulations Maël Lefeuvre, Marie-Claude Marsolier, Céline Bon This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7045281/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Mar, 2026 Read the published version in Genome Biology → Version 1 posted 12 You are reading this latest preprint version Abstract Background: Recent advancements in paleogenetics, coupled with the emergence of dedicated statistical methods have, in recent years, streamlined the detection of close genetic ties from ancient DNA samples, leading to a substantial surge in scientific publications emphasizing the reconstruction of genealogies within archaeological funerary contexts. However, while these methods all claim aptitude for addressing the inherent biases of ancient DNA, assessing their practical reliability can often be challenging, particularly in case studies involving few and/or poorly preserved samples. Furthermore, the genetic heritage and cultural practices of the population studied (e.g., inbreeding, endogamy) are factors which are often both complex to estimate and capable of impacting the accuracy of these methods. Results : We present an in-depth comparative study of six ancient DNA genetic relatedness estimation methods to precisely delineate their respective performance and behaviour across a range of five biological parameters: sample coverage, use of PMD-correction methods, human contamination, genetic diversity, and inbreeding. To this end, we developed ?BADGER? (Benchmark Ancient DNA GEnetic Relatedness), an automated pipeline and software which first simulates pedigrees using randomly selected present-day individuals from the 1000-genomes dataset, followed by raw ancient DNA sequences for each of the individuals composing these trees. Conclusions: The results of this benchmark enable us to discuss the individual strengths and limitations of these methods, propose a set of prescriptions to consider when interpreting their results and demonstrates that their reliability cannot be predicted from sample coverage alone, and may be subject to multiple sources of bias. genetic relatedness paleogenomic ancient DNA benchmarking pedigree in silico simulations Full Text Additional Declarations Competing interest reported. Maël Lefeuvre, Céline Bon and Marie-Claude Marsolier were instrumental in the development of one of the methods benchmarked within the present manuscript (GRUPS-rs), and are primary authors of its accompanying scientific publication. Supplementary Files supplementarymaterialsv1.0.0.pdf supplementarytablesv1.0.0.xlsx Cite Share Download PDF Status: Published Journal Publication published 09 Mar, 2026 Read the published version in Genome Biology → Version 1 posted Editorial decision: Revision requested 21 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviews received at journal 10 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers agreed at journal 27 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers invited by journal 22 Sep, 2025 Editor assigned by journal 07 Jul, 2025 Submission checks completed at journal 07 Jul, 2025 First submitted to journal 04 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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