| Title: | Open-source benchmarking of IBD segment detection methods for biobank-scale cohorts |
| Journal: | GigaScience |
| Published: | 6 Dec 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36472573/ |
| DOI: | https://doi.org/10.1093/gigascience/giac111 |
| URL: | https://academic.oup.com/gigascience/article-pdf/doi/10.1093/gigascience/giac111/48440393/giac111.pdf |
Publication 8048
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Abstract
In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of the power, accuracy, and resource consumption of these IBD segment detection methods using realistic population genetic simulations with various settings. Our results pave the road for fair evaluation of IBD segment detection methods and provide an practical guide for users.5 Authors
- Kecong Tang
- Ardalan Naseri
- Yuan Wei
- Shaojie Zhang
- Degui Zhi
1 Application
| Application ID | Title |
|---|---|
| 24247 | Searching Identity-by-descent segments in biobank-scale cohorts |
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