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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-8535381 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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