clusIBD: Robust Detection of Identity-by-descent Segments Using Unphased Genetic Data from Poor-quality Samples

Ran Li; Yu Zang; Zhentang Liu; Jingyi Yang; Nana Wang; Jiajun Liu; Enlin Wu; Riga Wu; Hongyu Sun

doi:10.1093/gpbjnl/qzaf055

clusIBD: Robust Detection of Identity-by-descent Segments Using Unphased Genetic Data from Poor-quality Samples

Genomics Proteomics Bioinformatics. 2025 Jun 20:qzaf055. doi: 10.1093/gpbjnl/qzaf055. Online ahead of print.

Authors

Ran Li^{1

2

3}, Yu Zang^{1

3}, Zhentang Liu^{1

3}, Jingyi Yang^{1

3}, Nana Wang^{1

3}, Jiajun Liu^{1

3}, Enlin Wu^{1

3}, Riga Wu^{1

3}, Hongyu Sun^{1

3}

Affiliations

¹ Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.
² School of Medicine, Jiaying University, Meizhou 514015, China.
³ Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou 510080, China.

PMID: 40578321
DOI: 10.1093/gpbjnl/qzaf055

Abstract

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 genotype 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 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).

Keywords: Algorithm; Identity by descent; Kinship inference; Poor-quality samples; Unphased genetic data.

© The Author(s) 2025. Published by Oxford University Press and Science Press on behalf of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China.