Literature DB >> 23948322

The interpretation of single source and mixed DNA profiles.

Duncan Taylor1, Jo-Anne Bright, John Buckleton.   

Abstract

A method for interpreting autosomal mixed DNA profiles based on continuous modelling of peak heights is described. MCMC is applied with a model for allelic and stutter heights to produce a probability for the data given a specified genotype combination. The theory extends to handle any number of contributors and replicates, although practical implementation limits analyses to four contributors. The probability of the peak data given a genotype combination has proven to be a highly intuitive probability that may be assessed subjectively by experienced caseworkers. Whilst caseworkers will not assess the probabilities per se, they can broadly judge genotypes that fit the observed data well, and those that fit relatively less well. These probabilities are used when calculating a subsequent likelihood ratio. The method has been trialled on a number of mixed DNA profiles constructed from known contributors. The results have been assessed against a binary approach and also compared with the subjective judgement of an analyst.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Continuous models; Forensic DNA interpretation; Low template DNA; Mixtures

Mesh:

Substances:

Year:  2013        PMID: 23948322     DOI: 10.1016/j.fsigen.2013.05.011

Source DB:  PubMed          Journal:  Forensic Sci Int Genet        ISSN: 1872-4973            Impact factor:   4.882


  17 in total

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Review 2.  The future of forensic DNA analysis.

Authors:  John M Butler
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-08-05       Impact factor: 6.237

3.  Towards developing forensically relevant single-cell pipelines by incorporating direct-to-PCR extraction: compatibility, signal quality, and allele detection.

Authors:  Nidhi Sheth; Harish Swaminathan; Amanda J Gonzalez; Ken R Duffy; Catherine M Grgicak
Journal:  Int J Legal Med       Date:  2021-01-23       Impact factor: 2.686

4.  The factor of 10 in forensic DNA match probabilities.

Authors:  Simone Gittelson; Tamyra R Moretti; Anthony J Onorato; Bruce Budowle; Bruce S Weir; John Buckleton
Journal:  Forensic Sci Int Genet       Date:  2017-02-16       Impact factor: 4.882

Review 5.  Separation/extraction, detection, and interpretation of DNA mixtures in forensic science (review).

Authors:  Ruiyang Tao; Shouyu Wang; Jiashuo Zhang; Jingyi Zhang; Zihao Yang; Xiang Sheng; Yiping Hou; Suhua Zhang; Chengtao Li
Journal:  Int J Legal Med       Date:  2018-05-25       Impact factor: 2.686

6.  Open practices in our science and our courtrooms.

Authors:  Michael D Edge; Jeanna Neefe Matthews
Journal:  Trends Genet       Date:  2021-11-02       Impact factor: 11.821

7.  Four model variants within a continuous forensic DNA mixture interpretation framework: Effects on evidential inference and reporting.

Authors:  Harish Swaminathan; Muhammad O Qureshi; Catherine M Grgicak; Ken Duffy; Desmond S Lun
Journal:  PLoS One       Date:  2018-11-20       Impact factor: 3.240

8.  Evaluation of forensic DNA mixture evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion.

Authors:  Frederick R Bieber; John S Buckleton; Bruce Budowle; John M Butler; Michael D Coble
Journal:  BMC Genet       Date:  2016-08-31       Impact factor: 2.797

9.  Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model.

Authors:  Sho Manabe; Chie Morimoto; Yuya Hamano; Shuntaro Fujimoto; Keiji Tamaki
Journal:  PLoS One       Date:  2017-11-17       Impact factor: 3.240

10.  Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles.

Authors:  Keith Inman; Norah Rudin; Ken Cheng; Chris Robinson; Adam Kirschner; Luke Inman-Semerau; Kirk E Lohmueller
Journal:  BMC Bioinformatics       Date:  2015-09-18       Impact factor: 3.169

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