A top-down approach to DNA mixtures

Slooten, Klaas

doi:10.1016/j.fsigen.2020.102250

Cited by 14 publications

(8 citation statements)

References 30 publications

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“…In some cases it is only possible to interpret the major contributor(s) of the DNA mixture. If minor contributors are not of interest, the NOC can be based upon the former, and this helps to simplify the model [72,74].…”

Section: Number Of Contributors (Noc)mentioning

confidence: 99%

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A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Gill

Benschop

Buckleton

et al. 2021

Genes

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Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.

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Section: Number Of Contributors (Noc)mentioning

confidence: 99%

“…Another database searching tool available in STRmix™ is to carry out a top-down analysis [74] in which only the main contributors to a highly complex profile are compared. In concept, a top-down analysis is similar to carrying out an evaluation on a major 'cluster' of peaks in a profile [194].…”

Section: Lr Calculationmentioning

confidence: 99%

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

Gill

Benschop

Buckleton

et al. 2021

Genes

View full text Add to dashboard Cite

show abstract

“…Similar contributions, in particular, have examined how forensic genetics' original difficulties developed, eventually, a complicated set of methodologies were used to resolve the issue that focuses on ensuring the forensic DNA evidence's reliability and credibility [22]. Moreover, the transnational DNA data exchange provides ethical challenges that have received limited attention in STS contributions thus far [23,24].…”

Section: Ethical Challenges Of Transnational Dna Data Exchangementioning

confidence: 99%

A Study on DNA Profiling Techniques and Transnational Exchange of DNA Data from Databank

Padmanabhan¹,

Sapna²

2022

RIA

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DNA technology has shown to be a valuable investigative tool in the release of innocent people and the identification of those responsible for serious crimes. In the battle against illegal immigration, cross-border crime, and terrorism, the transnational DNA data interchange from national DNA databanks has become a current trend. The data types that can be shared and the system is managed by a national authority are governed by individual national legislation, which determines the scope of the data exchange. Furthermore, one of the most difficult problems in forensic science is DNA profiling, and it is a hotly debated topic. The number of unknowns in a combination raises the computational difficulty of DNA profiling dramatically. To overcome this issue, various approaches have been designed and implemented. As a result, we examine DNA profiling methodologies and tools in this study, focusing on their computational accuracy and performance. Furthermore, this research examines the available data on DNA exchange and comparison across borders. We hope this review provides more ideas for future research to choose efficient profiling techniques.

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“…Comparison of different published approaches is confounded by the use of different multiplexes and sample types and also by the use of different metrics to score success. In casework there is no well-defined concept of the true number of contributors [15,16]. When using ground truth known samples as in validation studies, we have the benefit of knowing experimental NoC; that is the number of individual contributor's DNA that was added to the PCR reaction.…”

Section: Introductionmentioning

confidence: 99%

Estimating the number of contributors to a DNA profile using decision trees

Kruijver

Kelly

Cheng

et al. 2021

Forensic Science International: Genetics

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The interpretation of DNA profiles typically starts with an assessment of the number of contributors. In the last two decades, several methods have been proposed to assist with this assessment. We describe a relatively simple method using decision trees, that is fast to run and fully transparent to a forensic analyst. We use mixtures from the publicly available PROVEDIt dataset to demonstrate the performance of the method. We show that the performance of the method crucially depends on the performance of filters for stutter and other artefacts. We compare the performance of the decision tree method with other published methods for the same dataset.

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A top-down approach to DNA mixtures

Cited by 14 publications

References 30 publications

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™

A Study on DNA Profiling Techniques and Transnational Exchange of DNA Data from Databank

Estimating the number of contributors to a DNA profile using decision trees

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