总等位基因计数分布(TAC曲线)改善了复杂DNA混合物的贡献者数量估计

IF 0.2 Q4 MEDICINE, LEGAL
Josée Noël, S. Noël, F. Mailly, Dominic Granger, J. Lefebvre, E. Milot, Diane Séguin
{"title":"总等位基因计数分布(TAC曲线)改善了复杂DNA混合物的贡献者数量估计","authors":"Josée Noël, S. Noël, F. Mailly, Dominic Granger, J. Lefebvre, E. Milot, Diane Séguin","doi":"10.1080/00085030.2022.2028359","DOIUrl":null,"url":null,"abstract":"Abstract As the forensic community is transitioning to probabilistic genotyping and the use of likelihood ratios to assign probative weight to DNA mixtures, the assessment of the number of contributors (NOC) needs to be more robust for mixture interpretation. However, NOC assessment can be challenging for low-template and/or high order mixtures. Here, we present a quick and easy-to-use tool to help with NOC estimation: total allele count curves (TAC curves). TAC curves for two to seven contributors were generated using sets of 20,000 in silico mixtures, for five populations (African American, Caucasian, Asian, Apache and Native Alaska) and for commonly used commercial STR kits (GlobalFilerTM, PowerPlex® Fusion, PowerPlex® ESX 17 and IdentifilerTM). To assess the performance of TAC curves, the NOC was evaluated for 80 mixtures, with and without use of the curves. Results show that TAC curves allow for a better NOC assessment as correct evaluations rose from 10% when using maximal allele count (MAC) to 65% when also using TAC for four to six contributor mixtures. Supplemental data for this article is available online at http://dx.doi.org/10.1080/00085030.2022.2028359 .","PeriodicalId":44383,"journal":{"name":"Canadian Society of Forensic Science Journal","volume":"55 1","pages":"156 - 170"},"PeriodicalIF":0.2000,"publicationDate":"2022-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Total allele count distribution (TAC curves) improves number of contributor estimation for complex DNA mixtures\",\"authors\":\"Josée Noël, S. Noël, F. Mailly, Dominic Granger, J. Lefebvre, E. Milot, Diane Séguin\",\"doi\":\"10.1080/00085030.2022.2028359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract As the forensic community is transitioning to probabilistic genotyping and the use of likelihood ratios to assign probative weight to DNA mixtures, the assessment of the number of contributors (NOC) needs to be more robust for mixture interpretation. However, NOC assessment can be challenging for low-template and/or high order mixtures. Here, we present a quick and easy-to-use tool to help with NOC estimation: total allele count curves (TAC curves). TAC curves for two to seven contributors were generated using sets of 20,000 in silico mixtures, for five populations (African American, Caucasian, Asian, Apache and Native Alaska) and for commonly used commercial STR kits (GlobalFilerTM, PowerPlex® Fusion, PowerPlex® ESX 17 and IdentifilerTM). To assess the performance of TAC curves, the NOC was evaluated for 80 mixtures, with and without use of the curves. Results show that TAC curves allow for a better NOC assessment as correct evaluations rose from 10% when using maximal allele count (MAC) to 65% when also using TAC for four to six contributor mixtures. Supplemental data for this article is available online at http://dx.doi.org/10.1080/00085030.2022.2028359 .\",\"PeriodicalId\":44383,\"journal\":{\"name\":\"Canadian Society of Forensic Science Journal\",\"volume\":\"55 1\",\"pages\":\"156 - 170\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2022-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Society of Forensic Science Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/00085030.2022.2028359\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MEDICINE, LEGAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Society of Forensic Science Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00085030.2022.2028359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MEDICINE, LEGAL","Score":null,"Total":0}
引用次数: 2

摘要

摘要随着法医学界正在向概率基因分型和使用似然比为DNA混合物分配证明权重过渡,对贡献者数量(NOC)的评估需要对混合物的解释更加稳健。然而,对于低模板和/或高阶混合物,NOC评估可能具有挑战性。在这里,我们提供了一个快速易用的工具来帮助NOC估计:总等位基因计数曲线(TAC曲线)。两到七个贡献者的TAC曲线是使用20000组计算机混合物生成的,用于五个群体(非裔美国人、高加索人、亚洲人、阿帕奇人和阿拉斯加原住民)和常用的商业STR试剂盒(GlobalFilerTM、PowerPlex®Fusion、PowerPlex™ESX 17和IdentifierTM)。为了评估TAC曲线的性能,在使用和不使用曲线的情况下,对80种混合物的NOC进行了评估。结果表明,TAC曲线允许更好的NOC评估,因为正确的评估从使用最大等位基因计数(MAC)时的10%上升到同样使用TAC的四至六个贡献者混合物时的65%。本文的补充数据可在线获取,网址为http://dx.doi.org/10.1080/00085030.2022.2028359。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Total allele count distribution (TAC curves) improves number of contributor estimation for complex DNA mixtures
Abstract As the forensic community is transitioning to probabilistic genotyping and the use of likelihood ratios to assign probative weight to DNA mixtures, the assessment of the number of contributors (NOC) needs to be more robust for mixture interpretation. However, NOC assessment can be challenging for low-template and/or high order mixtures. Here, we present a quick and easy-to-use tool to help with NOC estimation: total allele count curves (TAC curves). TAC curves for two to seven contributors were generated using sets of 20,000 in silico mixtures, for five populations (African American, Caucasian, Asian, Apache and Native Alaska) and for commonly used commercial STR kits (GlobalFilerTM, PowerPlex® Fusion, PowerPlex® ESX 17 and IdentifilerTM). To assess the performance of TAC curves, the NOC was evaluated for 80 mixtures, with and without use of the curves. Results show that TAC curves allow for a better NOC assessment as correct evaluations rose from 10% when using maximal allele count (MAC) to 65% when also using TAC for four to six contributor mixtures. Supplemental data for this article is available online at http://dx.doi.org/10.1080/00085030.2022.2028359 .
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.00
自引率
0.00%
发文量
21
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信