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dc.contributor.advisorCotton, Robinen_US
dc.contributor.authorRandolph, Briannaen_US
dc.date.accessioned2019-07-22T13:51:00Z
dc.date.available2019-07-22T13:51:00Z
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/2144/36616
dc.description.abstractUsing computer systems for probabilistic genotyping on DNA evidence in forensic casework is beneficial as it allows a complete analysis of the data available for a wide range of profiles, a range that is limited when analyzed manually. One such software, Bulletproof, uses the exact method as the statistical foundation of its web-based interface to estimate the likelihood ratio of two hypotheses that explain the given evidence. In this investigation, the capability of Bulletproof was examined by analyzing the effects of evidence and reference sample template amount, injection time, and stutter filter utilization on likelihood ratio. In terms of likelihood ratio, deconvolution by the software is more efficient in cases in which evidence samples of high contrast ratios (such as 1:9 vs. 1:1) and low contributor count have high template, and when sample injection times are low. Reference sample template amount and injection time are less impactful than that of evidentiary samples. As with unknown samples, reference samples should be analyzed beforehand and artifacts removed for better deconvolution.en_US
dc.language.isoen_US
dc.subjectMolecular biologyen_US
dc.subjectBulletproofen_US
dc.subjectDNAen_US
dc.subjectForensic scienceen_US
dc.subjectLikelihood ratioen_US
dc.subjectProbabilistic genotypingen_US
dc.subjectStutteren_US
dc.titleAn analysis of bulletproof as probabilistic genotyping software for forensic DNA analysis caseworken_US
dc.typeThesis/Dissertationen_US
dc.date.updated2019-06-14T16:03:12Z
etd.degree.nameMaster of Scienceen_US
etd.degree.levelmastersen_US
etd.degree.disciplineBiomedical Forensic Sciencesen_US
etd.degree.grantorBoston Universityen_US


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