Analytical validation of the IBD segment-based tool KinSNP® for human identification applications.

IF 2.2 4区 工程技术 Q3 BIOCHEMICAL RESEARCH METHODS BioTechniques Pub Date : 2025-01-18 DOI:10.1080/07366205.2025.2454770
Bruce Budowle, Jianye Ge, Lee Baker, Kristen Mittelman, David Mittelman
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Abstract

KinSNP® v1.0, a software tool for human identification, has been widely used to measure IBD segment sharing between individuals using dense SNP data. Herein, the tool was validated using simulated pedigree data (up to 9th degree relationships) from five diverse populations from the 1000 Genomes Project. Performance was further tested under conditions of simulated genotyping errors and allele or locus dropout. KinSNP data were benchmarked with IBIS, Ped-sim, and known ranges of centimorgan sharing. The calculated values from KinSNP aligned closely with IBIS and Ped-sim benchmarks, and accuracy was maintained with up to 75% simulated missing data. However, even slight increases in simulated sequence error rates negatively impacted performance. This study supports that KinSNP is a reliable solution for IBD-based analyses in forensic contexts.

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基于IBD片段的工具KinSNP®用于人类鉴定应用的分析验证。
KinSNP®v1.0是一种用于人类鉴定的软件工具,已广泛用于使用密集的SNP数据来测量个体之间的IBD片段共享。在此,该工具使用来自1000基因组计划的五个不同人群的模拟系谱数据(高达9度关系)进行验证。在模拟基因分型错误和等位基因或基因座缺失的条件下进一步测试性能。KinSNP数据以IBIS、Ped-sim和已知的centimorgan共享范围为基准。KinSNP的计算值与IBIS和Ped-sim基准非常接近,并且在高达75%的模拟缺失数据下保持准确性。然而,即使是模拟序列错误率的轻微增加也会对性能产生负面影响。该研究支持KinSNP是法医环境中基于ibd分析的可靠解决方案。
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来源期刊
BioTechniques
BioTechniques 工程技术-生化研究方法
CiteScore
4.40
自引率
0.00%
发文量
68
审稿时长
3.3 months
期刊介绍: BioTechniques is a peer-reviewed, open-access journal dedicated to publishing original laboratory methods, related technical and software tools, and methods-oriented review articles that are of broad interest to professional life scientists, as well as to scientists from other disciplines (e.g., chemistry, physics, computer science, plant and agricultural science and climate science) interested in life science applications for their technologies. Since 1983, BioTechniques has been a leading peer-reviewed journal for methods-related research. The journal considers: Reports describing innovative new methods, platforms and software, substantive modifications to existing methods, or innovative applications of existing methods, techniques & tools to new models or scientific questions Descriptions of technical tools that facilitate the design or performance of experiments or data analysis, such as software and simple laboratory devices Surveys of technical approaches related to broad fields of research Reviews discussing advancements in techniques and methods related to broad fields of research Letters to the Editor and Expert Opinions highlighting interesting observations or cautionary tales concerning experimental design, methodology or analysis.
期刊最新文献
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