Calculation of the Weight of Evidence for Combined Single-Cell and Extracellular Forensic DNA

IF 3.6 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS IEEE/ACM Transactions on Computational Biology and Bioinformatics Pub Date : 2024-06-19 DOI:10.1109/TCBB.2024.3416877
Desmond S. Lun;Catherine M. Grgicak
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Abstract

The weight of DNA evidence for forensic applications is typically assessed through the calculation of the likelihood ratio (LR). In the standard workflow, DNA is extracted from a collection of cells where the cells of an unknown number of donors are mixed. The DNA is then genotyped, and the LR is calculated through well-established methods. Recently, a method for calculating the LR from single-cell data has been presented. Rather than extracting the DNA while the cells are still mixed, single-cell data is procured by first isolating each cell. Extraction and fragment analysis of relevant forensic loci follows such that individual cells are genotyped. This workflow leads to significantly stronger weights of evidence, but it does not account for extracellular DNA that could also be present in the sample. In this paper, we present a method for calculation of an LR that combines single-cell and extracellular data. We demonstrate the calculation on example data and show that the combined LR can lead to stronger conclusions than would be obtained from calculating LRs on the single-cell and extracellular DNA separately.
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计算单细胞和细胞外法医 DNA 的综合证据权重。
法医应用中 DNA 证据的权重通常通过计算似然比 (LR) 来评估。在标准工作流程中,DNA 从细胞集合中提取,其中混合了未知数量供体的细胞。然后对 DNA 进行基因分型,并通过成熟的方法计算 LR。最近,有人提出了一种从单细胞数据计算 LR 的方法。这种方法不是在细胞仍处于混合状态时提取 DNA,而是先分离每个细胞,然后获取单细胞数据。随后对相关法医位点进行提取和片段分析,从而对单个细胞进行基因分型。这种工作流程可大大提高证据的权重,但却无法考虑样本中可能存在的细胞外 DNA。本文介绍了一种结合单细胞和细胞外数据计算 LR 的方法。我们在实例数据上演示了计算方法,结果表明,与分别计算单细胞和细胞外 DNA 的 LR 相比,综合 LR 能得出更有力的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
479
审稿时长
3 months
期刊介绍: IEEE/ACM Transactions on Computational Biology and Bioinformatics emphasizes the algorithmic, mathematical, statistical and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development of biological databases; and important biological results that are obtained from the use of these methods, programs and databases; the emerging field of Systems Biology, where many forms of data are used to create a computer-based model of a complex biological system
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