Bleka Øyvind, Dørum Guro, Haned Hinda, Gill Peter
Department of Forensic Genetics, Norwegian Institute of Public Health, Oslo, Norway.
Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.
Forensic Sci Int Genet. 2014 Mar;9:134-41. doi: 10.1016/j.fsigen.2013.11.006. Epub 2013 Dec 11.
Often in forensic cases, the profile of at least one of the contributors to a DNA evidence sample is unknown and a database search is needed to discover possible perpetrators. In this article we consider two types of search strategies to extract suspects from a database using methods based on probability arguments. The performance of the proposed match scores is demonstrated by carrying out a study of each match score relative to the level of allele drop-out in the crime sample, simulating low-template DNA. The efficiency was measured by random man simulation and we compared the performance using the SGM Plus kit and the ESX 17 kit for the Norwegian population, demonstrating that the latter has greatly enhanced power to discover perpetrators of crime in large national DNA databases. The code for the database extraction strategies will be prepared for release in the R-package forensim.
在法医案件中，DNA证据样本的至少一名贡献者的基因分型通常是未知的，因此需要进行数据库搜索以找出可能的犯罪者。在本文中，我们考虑了两种搜索策略，即使用基于概率论证的方法从数据库中提取嫌疑人。通过对每个匹配分数相对于犯罪样本中等位基因缺失水平进行研究来证明所提出的匹配分数的性能，模拟低模板DNA。通过随机个体模拟来衡量效率，并且我们比较了挪威人群使用SGM Plus试剂盒和ESX 17试剂盒的性能，表明后者在大型国家DNA数据库中发现犯罪者的能力有了极大提高。数据库提取策略的代码将准备好在R包forensim中发布。
