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

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 de...

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Autores principales: Gill, Peter, Benschop, Corina, Buckleton, John, Bleka, Øyvind, Taylor, Duncan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8535381/
https://www.ncbi.nlm.nih.gov/pubmed/34680954
http://dx.doi.org/10.3390/genes12101559
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author Gill, Peter
Benschop, Corina
Buckleton, John
Bleka, Øyvind
Taylor, Duncan
author_facet Gill, Peter
Benschop, Corina
Buckleton, John
Bleka, Øyvind
Taylor, Duncan
author_sort Gill, Peter
collection PubMed
description 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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spelling pubmed-85353812021-10-23 A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™ Gill, Peter Benschop, Corina Buckleton, John Bleka, Øyvind Taylor, Duncan Genes (Basel) Review 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. MDPI 2021-09-30 /pmc/articles/PMC8535381/ /pubmed/34680954 http://dx.doi.org/10.3390/genes12101559 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Gill, Peter
Benschop, Corina
Buckleton, John
Bleka, Øyvind
Taylor, Duncan
A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™
title A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™
title_full A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™
title_fullStr A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™
title_full_unstemmed A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™
title_short A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™
title_sort review of probabilistic genotyping systems: euroformix, dnastatistx and strmix™
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8535381/
https://www.ncbi.nlm.nih.gov/pubmed/34680954
http://dx.doi.org/10.3390/genes12101559
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