The impact of parameter variation in the quantification of forensic genetic evidence
Abstract Technological advancements have allowed the detection of increasingly complex forensic genetics samples, as minimum amounts of DNA can now be detected in crime scenes or other settings of interest. The weight of the evidence depends on several parameters regarding the population and sample-...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-83841-2 |
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| author | Camila Costa Carolina Figueiredo Sandra Costa Paulo Miguel Ferreira António Amorim Lourdes Prieto Nádia Pinto |
| author_facet | Camila Costa Carolina Figueiredo Sandra Costa Paulo Miguel Ferreira António Amorim Lourdes Prieto Nádia Pinto |
| author_sort | Camila Costa |
| collection | DOAJ |
| description | Abstract Technological advancements have allowed the detection of increasingly complex forensic genetics samples, as minimum amounts of DNA can now be detected in crime scenes or other settings of interest. The weight of the evidence depends on several parameters regarding the population and sample-related analytical factors, the latter in a greater number when the DNA amount is considered. This led to the development of probabilistic genotyping software (PGS), able to deal with the associated complexities. This study aims to evaluate the impact on the evidence’s weighing, when different analytical threshold values are used, and when different models and/or estimates for analytical artifacts, such as stutters or drop-in parameters, are considered. To reach this goal, three PGS, based on different statistical models, were used to analyze real casework pairs of samples composed of a mixture with either two or three estimated contributors, and a single-source sample associated. The obtained results show that the estimation of these parameters must not be overlooked, as they may considerably impact the outcome. This underlines the importance of proper parametrization in the analysis of forensic genetics identification problems when using complex samples, and the understanding by practitioners of how probabilistic genotyping informatics tools work to use them accurately. |
| format | Article |
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| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-81bf56bf7a7f429abc523ae38800d7482025-01-26T12:26:43ZengNature PortfolioScientific Reports2045-23222025-01-0115111210.1038/s41598-024-83841-2The impact of parameter variation in the quantification of forensic genetic evidenceCamila Costa0Carolina Figueiredo1Sandra Costa2Paulo Miguel Ferreira3António Amorim4Lourdes Prieto5Nádia Pinto6Departamento de Biologia, Faculdade de Ciências, Universidade do PortoDepartamento de Biologia, Faculdade de Ciências, Universidade do PortoBiologia, Laboratório de Polícia Científica da Polícia Judiciaria (LPC-PJ)Biologia, Laboratório de Polícia Científica da Polícia Judiciaria (LPC-PJ)Departamento de Biologia, Faculdade de Ciências, Universidade do PortoGrupo de Medicina Xenómica, Instituto de Ciencias Forenses, Universidad de Santiago de Compostelai3S - Instituto de Investigação e Inovação em Saúde, Universidade do PortoAbstract Technological advancements have allowed the detection of increasingly complex forensic genetics samples, as minimum amounts of DNA can now be detected in crime scenes or other settings of interest. The weight of the evidence depends on several parameters regarding the population and sample-related analytical factors, the latter in a greater number when the DNA amount is considered. This led to the development of probabilistic genotyping software (PGS), able to deal with the associated complexities. This study aims to evaluate the impact on the evidence’s weighing, when different analytical threshold values are used, and when different models and/or estimates for analytical artifacts, such as stutters or drop-in parameters, are considered. To reach this goal, three PGS, based on different statistical models, were used to analyze real casework pairs of samples composed of a mixture with either two or three estimated contributors, and a single-source sample associated. The obtained results show that the estimation of these parameters must not be overlooked, as they may considerably impact the outcome. This underlines the importance of proper parametrization in the analysis of forensic genetics identification problems when using complex samples, and the understanding by practitioners of how probabilistic genotyping informatics tools work to use them accurately.https://doi.org/10.1038/s41598-024-83841-2Forensic DNAMixture samplesLikelihood ratioDrop-inAnalytical thresholdStutters |
| spellingShingle | Camila Costa Carolina Figueiredo Sandra Costa Paulo Miguel Ferreira António Amorim Lourdes Prieto Nádia Pinto The impact of parameter variation in the quantification of forensic genetic evidence Scientific Reports Forensic DNA Mixture samples Likelihood ratio Drop-in Analytical threshold Stutters |
| title | The impact of parameter variation in the quantification of forensic genetic evidence |
| title_full | The impact of parameter variation in the quantification of forensic genetic evidence |
| title_fullStr | The impact of parameter variation in the quantification of forensic genetic evidence |
| title_full_unstemmed | The impact of parameter variation in the quantification of forensic genetic evidence |
| title_short | The impact of parameter variation in the quantification of forensic genetic evidence |
| title_sort | impact of parameter variation in the quantification of forensic genetic evidence |
| topic | Forensic DNA Mixture samples Likelihood ratio Drop-in Analytical threshold Stutters |
| url | https://doi.org/10.1038/s41598-024-83841-2 |
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