Analyzing population structure for forensic STR markers in next generation sequencing data.

Analyzing population structure for forensic STR markers in next generation sequencing data.
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分析下一代测序数据中法医STR标记的种群结构。

DOI:
10.1016/j.fsigen.2020.102364
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发表时间:
2020-11
期刊:
Forensic science international. Genetics
影响因子:
--
通讯作者:
Weir BS
Weir BS
中科院分区:
其他
文献类型:
--
作者:
Aalbers SE;Hipp MJ;Kennedy SR;Weir BS

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在DNA证据图谱评估期间计算的匹配概率依赖于群体结构量θ的适当值。基于NGS的方法将增强法医鉴定,随着向这种方法的转变,需要促进基于NGS的群体遗传学分析。如果要将NGS数据用于匹配概率,则需要有一种方法来适应群体结构,这需要这些数据的θ值。目前还没有这种估计数。本研究评估人口结构的序列为基础的数据使用一个相对较新的方法,适用于STR数据超过27个位点在五个不同的地理群体。个体或群体之间的匹配比例用于获得位点特异性θ估计值以及每个地理群体和全球测量值的估计值。结果表明,测序数据对θ估计值的影响与基于CE的结果相似。
Match probabilities calculated during the evaluation of DNA evidence profiles rely on appropriate values of the population structure quantity θ. NGS-based methods will enhance forensic identification and with the transformation to such methods comes the need to facilitate NGS-based population genetics analysis. If NGS data are to be used for match probabilities there needs to be a way to accommodate population structure, which requires values for θ for those data. Such estimates have not been available. This study assesses population structure for sequence-based data using a relatively new approach applied to STR data over 27 loci in five different geographic groups. Matching proportions between individuals or groups are used to obtain locus-specific θ estimates as well as estimates per geographic group and a global measure. The results demonstrate similar effects of sequencing data on θ estimates compared to what has been seen for CE-based results.
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