Norsworthy Sarah, Lun Desmond S, Grgicak Catherine M
Biomedical Forensic Sciences Program, Boston University School of Medicine, Boston, MA 02118, USA.
Center for Computational and Integrative Biology, Rutgers University, Camden, NJ 08102, USA; Department of Computer Science, Rutgers University, Camden, NJ 08102, USA; Department of Plant Biology and Pathology, Rutgers University, New Brunswick, NJ 08901, USA.
Leg Med (Tokyo). 2018 May;32:1-8. doi: 10.1016/j.legalmed.2018.02.001. Epub 2018 Feb 8.
The interpretation of DNA evidence may rely upon the assumption that the forensic short tandem repeat (STR) profile is composed of multiple genotypes, or partial genotypes, originating from n contributors. In cases where the number of contributors (NOC) is in dispute, it may be justifiable to compute likelihood ratios that utilize different NOC parameters in the numerator and denominator, or present different likelihoods separately. Therefore, in this work, we evaluate the impact of allele dropout on estimating the NOC for simulated mixtures with up to six contributors in the presence or absence of a major contributor. These simulations demonstrate that in the presence of dropout, or with the application of an analytical threshold (AT), estimating the NOC using counting methods was unreliable for mixtures containing one or more minor contributors present at low levels. The number of misidentifications was only slightly reduced when we expand the number of STR loci from 16 to 21. In many of the simulations tested herein, the minimum and actual NOC differed by more than two, suggesting that low-template, high-order mixtures with allele counts fewer than six may be originating from as many as four-, five-, or six-persons. Thus, there is justification for the use of differing or multiple assumptions on the NOC when computing the weight of DNA evidence for low-template mixtures, particularly when the peak heights are in the vicinity of the signal threshold or allele counting methods are the mechanism by which the NOC is assessed.
DNA证据的解释可能依赖于这样一种假设，即法医短串联重复序列（STR）图谱由源自n个贡献者的多个基因型或部分基因型组成。在贡献者数量（NOC）存在争议的情况下，在分子和分母中使用不同的NOC参数计算似然比，或者分别呈现不同的似然比，可能是合理的。因此，在这项工作中，我们评估了等位基因缺失对估计存在或不存在主要贡献者的情况下，模拟的多达六个贡献者的混合物的NOC的影响。这些模拟表明，在存在缺失或应用分析阈值（AT）的情况下，使用计数方法估计含有一个或多个低水平次要贡献者的混合物的NOC是不可靠的。当我们将STR基因座数量从16个增加到21个时，错误识别的数量仅略有减少。在本文测试的许多模拟中，最小NOC和实际NOC相差超过两个，这表明等位基因计数少于六个的低模板、高阶混合物可能源自多达四个人、五个人或六个人。因此，在计算低模板混合物的DNA证据权重时，特别是当峰高接近信号阈值或等位基因计数方法是评估NOC的机制时，有理由对NOC使用不同的或多个假设。
