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解读低模板 DNA 谱。

Interpreting low template DNA profiles.

机构信息

Department of Epidemiology and Public Health, Imperial College, St Mary's Campus, Norfolk Place, London W21PG, UK.

出版信息

Forensic Sci Int Genet. 2009 Dec;4(1):1-10. doi: 10.1016/j.fsigen.2009.03.003. Epub 2009 May 2.

DOI:10.1016/j.fsigen.2009.03.003
PMID:19948328
Abstract

We discuss the interpretation of DNA profiles obtained from low template DNA samples. The most important challenge to interpretation in this setting arises when either or both of "drop-out" and "drop-in" create discordances between the crime scene DNA profile and the DNA profile expected under the prosecution allegation. Stutter and unbalanced peak heights are also problematic, in addition to the effects of masking from the profile of a known contributor. We outline a framework for assessing such evidence, based on likelihood ratios that involve drop-out and drop-in probabilities, and apply it to two casework examples. Our framework extends previous work, including new approaches to modelling homozygote drop-out and uncertainty in allele calls for stutter, masking and near-threshold peaks. We show that some current approaches to interpretation, such as ignoring a discrepant locus or reporting a "Random Man Not Excluded" (RMNE) probability, can be systematically unfair to defendants, sometimes extremely so. We also show that the LR can depend strongly on the assumed value for the drop-out probability, and there is typically no approximation that is useful for all values. We illustrate that ignoring the possibility of drop-in is usually unfair to defendants, and argue that under circumstances in which the prosecution relies on drop-out, it may be unsatisfactory to ignore any possibility of drop-in.

摘要

我们讨论了从低模板 DNA 样本中获得的 DNA 图谱的解释。在这种情况下,解释最具挑战性的是“缺失”和“插入”都导致犯罪现场 DNA 图谱与检方指控下预期的 DNA 图谱之间存在不一致,或者其中之一造成这种不一致。除了已知供体图谱的掩盖效应外,等位基因峰高的不稳定和不平衡也存在问题。我们概述了一种基于涉及缺失和插入概率的似然比来评估此类证据的框架,并将其应用于两个案例研究示例。我们的框架扩展了以前的工作,包括对纯合子缺失建模以及等位基因峰不稳定、掩盖和接近阈值的不确定性的新方法。我们表明,一些当前的解释方法,例如忽略不一致的基因座或报告“随机男子未排除”(Random Man Not Excluded,RMNE)概率,可能对被告不公平,有时甚至是极其不公平的。我们还表明,LR 强烈依赖于缺失概率的假设值,通常没有适用于所有值的近似值。我们说明忽略插入的可能性通常对被告不公平,并认为在检方依赖缺失的情况下,忽略任何插入的可能性可能是令人不满意的。

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