Near perfect identification of half sibling versus niece/nephew avuncular pairs without pedigree information or genotyped relatives

We present a novel computational framework that achieves near-complete separation of HS and N/A pairs using only genotype data. Our approach utilizes across-chromosome phasing to derive haplotype-level sharing features that summarize how IBD is distributed across parental homologues. By modeling these features with a Gaussian mixture model (GMM), we demonstrate near-perfect classification accuracy (> 98%) in biobank-scale data. Furthermore, we show that these high-confidence relationship labels can serve as long-range phasing anchors, providing structural constraints that improve the accuracy of across-chromosome homologue assignment. This method provides a robust, scalable solution for pedigree reconstruction and the control of cryptic relatedness in large-scale genomic studies.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-01-07
DOI
https://doi.org/10.64898/2026.01.06.697070
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Near perfect identification of half sibling versus niece/nephew avuncular pairs without pedigree information or genotyped relatives

Kristen M. Kelly, Emmanuel Sapin, Matthew C Keller
bioRxiv (Cold Spring Harbor Laboratory)
Genetic Associations and Epidemiology
article

Near perfect identification of half sibling versus niece/nephew avuncular pairs without pedigree information or genotyped relatives

Kristen M. Kelly, Emmanuel Sapin, Matthew C Keller
article en

Abstract

We present a novel computational framework that achieves near-complete separation of HS and N/A pairs using only genotype data. Our approach utilizes across-chromosome phasing to derive haplotype-level sharing features that summarize how IBD is distributed across parental homologues. By modeling these features with a Gaussian mixture model (GMM), we demonstrate near-perfect classification accuracy (> 98%) in biobank-scale data. Furthermore, we show that these high-confidence relationship labels can serve as long-range phasing anchors, providing structural constraints that improve the accuracy of across-chromosome homologue assignment. This method provides a robust, scalable solution for pedigree reconstruction and the control of cryptic relatedness in large-scale genomic studies.

bioRxiv (Cold Spring Harbor Laboratory)
University of Colorado Boulder (US), University of Colorado System (US)
Good health and well-being
Openalex Percentile: Top 96%
Genetic Associations and Epidemiology
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