基因分型
可靠性(半导体)
概率逻辑
统计
人口
计算机科学
口译(哲学)
计算生物学
可靠性工程
遗传学
生物
数学
医学
工程类
基因型
物理
基因
功率(物理)
程序设计语言
环境卫生
量子力学
作者
Safia Boodoosingh,Hannah Kelly,James M. Curran,Tim Kalafut
标识
DOI:10.1016/j.fsigen.2024.103046
摘要
Probabilistic genotyping (PG) is becoming the preferred standard for evidence interpretation, amongst forensic DNA laboratories, especially those in the United States. Various groups have expressed concern about reliability of PG systems, especially for mixtures beyond two contributors. Studies involving interlaboratory testing of known mixtures have been identified as ways to evaluate the reliability of PG systems. Reliability means different things in different contexts. However, it suffices here to think about it as a mixture of precision and accuracy. We might also consider whether a system is prone to producing misleading results - for example large likelihood ratios (LRs) when the POI is truly not a contributor, or small LRs when the POI is a truly a contributor. In this paper we show that the PG system STRmix™ is relatively unaffected by differences in parameter settings. That is, a DNA mixture that is analyzed in different laboratories using STRmix™ will result in different LRs, but less than 0.05% of these LRs would result in a different, or misleading conclusion as long as the LR is greater than 50. For the purposes of this study, we define LRs assigned using different parameters for the same mixtures as similar if the LR of the true POI is greater than the LRs generated for 99.9% of the general population. These findings are based on an interlaboratory study involving eight laboratories that provided twenty known DNA mixtures of two to four contributors and their individual laboratory STRmix™ parameters. The eight sets of laboratory parameters included differences in STR kits and PCR cycles as well as the peak, stutter, and locus specific amplification efficiency variances.
科研通智能强力驱动
Strongly Powered by AbleSci AI