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评估在 SNP 数量减少和基因分型错误增加情况下的四种法医学家系调查遗传分析方法。

Evaluation of Four Forensic Investigative Genetic Genealogy Analysis Approaches with Decreased Numbers of SNPs and Increased Genotyping Errors.

机构信息

Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China.

Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-Sen University, Guangzhou 510080, China.

出版信息

Genes (Basel). 2024 Oct 15;15(10):1329. doi: 10.3390/genes15101329.

Abstract

: Forensic investigative genetic genealogy (FIGG) has developed rapidly in recent years and is considered a novel tool for crime investigation. However, crime scene samples are often of low quality and quantity and are challenging to analyze. Deciding which approach should be used for kinship inference in forensic practice remains a troubling problem for investigators. : In this study, we selected four popular approaches-KING, IBS, TRUFFLE, and GERMLINE-comprising one method of moment (MoM) estimator and three identical by descent (IBD) segment-based tools and compared their performance at varying numbers of SNPs and levels of genotyping errors using both simulated and real family data. We also explored the possibility of making robust kinship inferences for samples with ultra-high genotyping errors by integrating MoM and the IBD segment-based methods. : The results showed that decreasing the number of SNPs had little effect on kinship inference when no fewer than 164 K SNPs were used for all four approaches. However, as the number decreased further, decreased efficiency was observed for the three IBD segment-based methods. Genotyping errors also had a significant effect on kinship inference, especially when they exceeded 1%. In contrast, MoM was much more robust to genotyping errors. Furthermore, the combination of the MoM and the IBD segment-based methods showed a higher overall accuracy, indicating its potential to improve the tolerance to genotyping errors. : In conclusion, this study shows that different approaches have unique characteristics and should be selected for different scenarios. More importantly, the integration of the MoM and the IBD segment-based methods can improve the robustness of kinship inference and has great potential for applications in forensic practice.

摘要

法医调查遗传基因学(FIGG)近年来发展迅速,被认为是犯罪调查的一种新工具。然而,犯罪现场样本通常质量和数量都较低,难以分析。在法医实践中,决定应该使用哪种方法进行亲属关系推断仍然是调查人员面临的一个难题。

在这项研究中,我们选择了四种流行的方法——KING、IBS、TRUFFLE 和 GERMLINE,包括一种矩估计方法(MoM)和三种基于相同来源的(IBD)片段工具,并使用模拟和真实家庭数据比较了它们在不同 SNP 数量和不同程度的基因分型错误下的性能。我们还探索了通过整合 MoM 和基于 IBD 片段的方法,对具有超高基因分型错误的样本进行稳健亲属关系推断的可能性。

结果表明,当所有四种方法都使用不少于 164 K SNP 时,减少 SNP 的数量对亲属关系推断的影响很小。然而,当数量进一步减少时,三种基于 IBD 片段的方法的效率降低。基因分型错误对亲属关系推断也有显著影响,尤其是当它们超过 1%时。相比之下,MoM 对基因分型错误的稳健性要高得多。此外,MoM 和基于 IBD 片段的方法的组合显示出更高的总体准确性,表明其有潜力提高对基因分型错误的容忍度。

综上所述,本研究表明,不同的方法具有独特的特点,应根据不同的情况选择。更重要的是,MoM 和基于 IBD 片段的方法的集成可以提高亲属关系推断的稳健性,在法医实践中有很大的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3add/11507463/b98a02cf6de4/genes-15-01329-g001.jpg

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