| Title: | Biobank-scale inference of multi-individual identity by descent and gene conversion |
| Journal: | American Journal of Human Genetics |
| Published: | 20 Mar 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38513668/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2024.02.015 |
| URL: | https://doi.org/10.1101/2023.11.03.565574 |
Publication 10089
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Abstract
We present a method for efficiently identifying clusters of identical-by-descent haplotypes in biobank-scale sequence data. Our multi-individual approach enables much more computationally efficient inference of identity by descent (IBD) than approaches that infer pairwise IBD segments and provides locus-specific IBD clusters rather than IBD segments. Our method's computation time, memory requirements, and output size scale linearly with the number of individuals in the dataset. We also present a method for using multi-individual IBD to detect alleles changed by gene conversion. Application of our methods to the autosomal sequence data for 125,361 White British individuals in the UK Biobank detects more than 9 million converted alleles. This is 2,900 times more alleles changed by gene conversion than were detected in a previous analysis of familial data. We estimate that more than 250,000 sequenced probands and a much larger number of additional genomes from multi-generational family members would be required to find a similar number of alleles changed by gene conversion using a family-based approach. Our IBD clustering method is implemented in the open-source ibd-cluster software package.</p>
2 Authors
- Sharon R Browning
- Brian L Browning
1 Application
| Application ID | Title |
|---|---|
| 19934 | Statistical and Computational Genetics Methods Development |
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