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Distinguishing pedigree relationships using multi-way identical by descent sharing and sex-specific genetic maps

Ying Qiao, Jens Sannerud, Sayantani Basu-Roy, Caroline Hayward, View ORCID ProfileAmy L. Williams
doi: https://doi.org/10.1101/753343
Ying Qiao
1Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
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Jens Sannerud
1Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
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Sayantani Basu-Roy
1Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
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Caroline Hayward
2MRC Human Genetics Unit, MRC Institute of Genetic and Molecular Medicine, University of Edinburgh, Edinburgh, UK
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Amy L. Williams
1Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
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  • ORCID record for Amy L. Williams
  • For correspondence: alw289@cornell.edu
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Abstract

The proportion of samples with one or more close relatives in a genetic dataset increases rapidly with sample size, necessitating relatedness modeling and enabling pedigree-based analyses. Despite this, relatives are generally unreported and current inference methods typically detect only the degree of relatedness of sample pairs and not pedigree relationships. We developed CREST, an accurate and fast method that identifies the pedigree relationships of close relatives. CREST utilizes identical by descent (IBD) segments shared between a pair of samples and their mutual relatives, leveraging the fact that sharing rates among these individuals differ across pedigree configurations. Furthermore, CREST exploits the profound differences in sex-specific genetic maps to classify pairs as maternally or paternally related—e.g., paternal half-siblings—using the locations of autosomal IBD segments shared between the pair. In simulated data, CREST correctly classifies 91.5-99.5% of grandparent-grandchild (GP) pairs, 70.5-97.0% of avuncular (AV) pairs, and 79.0-98.0% of half-siblings (HS) pairs compared to PADRE’s rates of 38.5-76.0% of GP, 60.5-92.0% of AV, 73.0-95.0% of HS pairs. Turning to the real 20,032 sample Generation Scotland (GS) dataset, CREST correctly determines the relationship of 99.0% of GP, 85.7% of AV, and 95.0% of HS pairs that have sufficient mutual relative data, completing this analysis in 10.1 CPU hours including IBD detection. CREST’s maternal and paternal relationship inference is also accurate, as it flagged five pairs as incorrectly labeled in the GS pedigrees— three of which we confirmed as mistakes, and two with an uncertain relationship—yielding 99.7% of HS and 93.5% of GP pairs correctly classified.

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Posted September 04, 2019.
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Distinguishing pedigree relationships using multi-way identical by descent sharing and sex-specific genetic maps
Ying Qiao, Jens Sannerud, Sayantani Basu-Roy, Caroline Hayward, Amy L. Williams
bioRxiv 753343; doi: https://doi.org/10.1101/753343
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Distinguishing pedigree relationships using multi-way identical by descent sharing and sex-specific genetic maps
Ying Qiao, Jens Sannerud, Sayantani Basu-Roy, Caroline Hayward, Amy L. Williams
bioRxiv 753343; doi: https://doi.org/10.1101/753343

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