Open-source benchmarking of IBD segment detection methods for biobank-scale cohorts

被引:8
|
作者
Tang, Kecong [1 ]
Naseri, Ardalan [2 ]
Wei, Yuan [1 ]
Zhang, Shaojie [1 ]
Zhi, Degui [2 ]
机构
[1] Univ Cent Florida, Dept Comp Sci, Orlando, FL 32816 USA
[2] Univ Texas Hlth Sci Ctr Houston, Sch Biomed Informat, Houston, TX 77030 USA
来源
GIGASCIENCE | 2022年 / 11卷
基金
美国国家卫生研究院;
关键词
identical-by-descent; biobank-scale data; IBD segment detection tools; benchmarking;
D O I
10.1093/gigascience/giac111
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:12
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