Instituto de Patologia e Imunologia Molecular da Universidade do Porto, R. Dr. Roberto Frias s/n, Porto, Portugal.
Int J Legal Med. 2011 Sep;125(5):629-36. doi: 10.1007/s00414-010-0472-2. Epub 2010 Jun 16.
Because of their sensitivity and high level of discrimination, short tandem repeat (STR) maker systems are currently the method of choice in routine forensic casework and data banking, usually in multiplexes up to 15-17 loci. Constraints related to sample amount and quality, frequently encountered in forensic casework, will not allow to change this picture in the near future, notwithstanding the technological developments. In this study, we present a free online calculator named PopAffiliator ( http://cracs.fc.up.pt/popaffiliator ) for individual population affiliation in the three main population groups, Eurasian, East Asian and sub-Saharan African, based on genotype profiles for the common set of STRs used in forensics. This calculator performs affiliation based on a model constructed using machine learning techniques. The model was constructed using a data set of approximately fifteen thousand individuals collected for this work. The accuracy of individual population affiliation is approximately 86%, showing that the common set of STRs routinely used in forensics provide a considerable amount of information for population assignment, in addition to being excellent for individual identification.
由于其灵敏度和高度的辨别力,短串联重复(STR)标记系统目前是常规法医工作和数据银行的首选方法,通常在多达 15-17 个基因座的多重分析中使用。与法医工作中经常遇到的样本量和质量有关的限制,尽管技术在不断发展,但在不久的将来也不会改变这种情况。在这项研究中,我们提出了一个免费的在线计算器,名为 PopAffiliator(http://cracs.fc.up.pt/popaffiliator),用于根据法医中常用的常见 STR 基因座的基因型谱对三个主要人群(欧亚人、东亚人和撒哈拉以南非洲人)进行个体群体归属。这个计算器是基于使用机器学习技术构建的模型来进行归属的。该模型是使用大约一万五千名为此项工作收集的个体数据构建的。个体群体归属的准确性约为 86%,这表明法医中常用的常见 STR 标记系统除了非常适合个体识别外,还为群体分配提供了相当多的信息。