Evidence map›Paper›PMID 42083796›Full record

ArticleBioinformatics (Oxford, England)2026

Fault-tolerant pedigree reconstruction from pairwise kinship relations.

Edward C Huang, Kevin A Li, Vagheesh M Narasimhan

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Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Edward C HuangDepartment of Computer Science, Stanford University, Stanford, CA 94305, United States.ORCID 0009-0000-2471-0531
Kevin A LiDepartment of Computer Science, The University of Texas at Austin, Austin, TX 78712, United States.ORCID 0009-0009-0446-6135
Vagheesh M NarasimhanDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712, United States.ORCID 0000-0001-8651-8844

Funding

Allen Discovery Center programNational Institute of General Medical Sciences of the National Institutes of HealthPaul G. Allen Frontiers Group advised program of the Paul G. Allen Family Foundation R35GM162367Texas Advanced Computing Center (TACC) at The University of Texas at Austin
6 · The paper itself

Abstract

motivationPedigrees reconstructed from biologically related ancient genomes have revealed many insights into (pre)history. To our knowledge, all reported ancient pedigrees have been primarily manually reconstructed, as existing pedigree reconstruction methods are ill-suited for the quality and nature of ancient DNA data.

resultsWe introduce repare, an open-source software method to automatically reconstruct pedigrees from inferred pairwise kinship relations, which are readily obtainable from ancient genomes. This method reconstructs pedigrees by iteratively incorporating pairwise kinship relations into a set of candidate pedigrees, with pruning and sampling to reduce its search space. It optionally considers supporting information such as haplogroups and skeletal age-at-death estimates. We evaluate this method on a variety of simulated pedigrees with varying error rates and missingness. We also use this method to reconstruct several published pedigrees that were originally manually reconstructed; for one, we present a potential alternative topology. repare optionally incorporates user-inferred pedigree constraints, enabling "human-in-the-loop" reconstruction workflows. Especially when used with these user-inferred constraints, we find that repare represents a powerful and flexible tool for ancient pedigree reconstruction. AVAILABILITY AND IMPLEMENTATION: repare is freely available at https://github.com/Narasimhan-Lab/repare. In addition, source code, benchmark scripts, and benchmark results used in this work are archived at https://doi.org/10.5281/zenodo.19716772.

Indexed as

PedigreeSoftwareAlgorithmsDNA, AncientHumansDNA, Ancient

Identifiers

PMID42083796
PMCPMC13293059

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.