Automated estimation of the number of contributors in autosomal STR profiles

Benschop, Corina C.G.; Backx, Anouk; Sijen, Titia

doi:10.1016/j.fsigss.2019.09.003

Cited by 5 publications

(4 citation statements)

References 3 publications

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“…Alternative methods using the total number of alleles (total allele count, TAC), the distribution of allele counts over the loci, the population's genotype frequencies, peak heights (PH), replicates, probability of allelic drop-out and stutter, or a Bayesian network approach have shown to yield improved NOC estimates [68,[79][80][81][82][83][84][85][86][87][88][89].…”

Section: Number Of Contributors (Noc)mentioning

confidence: 99%

“…Furthermore, DNAxs includes NOC tools based on a machine learning approach. These are designated as the RFC19 model that is specific to PowerPlex Fusion 6C (PPF6C) data as generated within NFI [89] and the generic RFC11 model which is laboratory independent [37]. The RFC19 model outperformed the MAC method and an in-house developed tool that utilised the TAC [89,91].…”

Section: Dnaxs and Related Modulesmentioning

confidence: 99%

“…These are designated as the RFC19 model that is specific to PowerPlex Fusion 6C (PPF6C) data as generated within NFI [89] and the generic RFC11 model which is laboratory independent [37]. The RFC19 model outperformed the MAC method and an in-house developed tool that utilised the TAC [89,91]. A drawback of such models is that it requires a large dataset for development and is specific to a laboratory's data.…”

Section: Dnaxs and Related Modulesmentioning

confidence: 99%

See 2 more Smart Citations

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%

Section: Dnaxs and Related Modulesmentioning

confidence: 99%

Section: Dnaxs and Related Modulesmentioning

confidence: 99%

See 1 more Smart Citation

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

Gill

Benschop

Buckleton

et al. 2021

Genes

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“…Finding the right cut point is the goal of the experiment. Compared with traditional experimental methods, it can provide a more stable and accurate acceleration model [8]. However, since the axial cutting depth is not taken into account, this method does not apply to changing the axial cutting depth.…”

Section: Numerical Control Cutting Experimentsmentioning

confidence: 99%

Influence of Numerical Control Cutting Parameters on Performance of Numerical Control Tool

Sha¹

2021

J. Phys.: Conf. Ser.

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As China has stepped into a new era of development, the popularity of computer applications is becoming more and more profound. Especially in the machinery manufacturing industry, the current market has put forward a higher requirement for the accuracy and toughness of machinery manufacturing, and the traditional artificial manufacturing has not been adapted to the development of the industry. Through numerical control technology, numerical control tool manufacturing process can become very standardized, its accuracy and toughness is also guaranteed. This paper will from the numerical control this point of view, to explore the influence of numerical control cutting parameters on the numerical control tool.

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