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clusIBD:Robust Detection of Identity-by-descent Segments Using Unphased Genetic Data from Poor-quality Samples
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作者 Ran Li Yu Zang +6 位作者 Zhentang Liu Jingyi Yang Nana Wang Jiajun Liu Enlin Wu Riga Wu Hongyu Sun 《Genomics, Proteomics & Bioinformatics》 2025年第3期59-70,共12页
The detection of identity-by-descent(IBD)segments is widely used to infer relatedness in many fields,including forensics and ancient DNA analysis.However,existing methods are often ineffective for poor-quality DNA sam... The detection of identity-by-descent(IBD)segments is widely used to infer relatedness in many fields,including forensics and ancient DNA analysis.However,existing methods are often ineffective for poor-quality DNA samples.Here,we propose a method,clusIBD,which can robustly detect IBD segments using unphased genetic data with a high rate of genotyping error.We evaluated and compared the performance of clusIBD with that of IBIS,TRUFFLE,and IBDseq using simulated data,artificial poor-quality materials,and ancient DNA samples.The results show that clusIBD outperforms these existing tools and could be used for kinship inference in fields such as ancient DNA analysis and criminal investigation.clusIBD is publicly available at GitHub(https://github.com/Ryan620/clusIBD/)and BioCode(https://ngdc.cncb.ac.cn/biocode/tool/BT007882). 展开更多
关键词 Identity-by-descent Kinship inference unphased genetic data Poor-quality sample Algorithm
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