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                            Library & Multimedia
 The A Posteriori Probability of the Number of Contributors When Conditioned on an Assumed Contributor
NCJ Number
              302390
Journal

*Forensic Science International: Genetics* Volume: 54 Dated: September 2021
Author(s)
          Catherine M. Grgicaka;
                        Ken R. Duffy;
                        Desmond S. Lunb
Date Published

September 2021
Annotation
              This article reports on the authors extension of their previous work on NOCIt, a Bayesian method that determines an A Posteriori Probability (APP) on the number of contributors (NOC) to a sample given an electropherogram, by reporting on an implementation where the user can add assumed contributors.
Abstract
              Forensic DNA signal is notoriously challenging to assess, requiring computational tools to support its interpretation. Over-expressions of stutter, allele drop-out, allele drop-in, degradation, differential degradation, and the like, make forensic DNA profiles too complicated to evaluate by manual methods. In response, computational tools that make point estimates on the Number of Contributors (NOC) to a sample have been developed, as have Bayesian methods that evaluate an A Posteriori Probability (APP) distribution on the NOC. In cases where an overly narrow NOC range is assumed, the downstream strength of evidence may be incomplete insofar as the evidence is evaluated with an inadequate set of propositions. NOCIt is a continuous system that incorporates models of peak height (including degradation and differential degradation), forward and reverse stutter, noise, and allelic drop-out, while being cognizant of allele frequencies in a reference population. When conditioned on a known contributor, this project found that the mode of the APP distribution can shift to one greater when compared with the circumstance where no known contributor is assumed, and that occurred most often when the assumed contributor was the minor constituent to the mixture. In a development of a result of Slooten and Caliebe (FSI:G, 2018) that, under suitable assumptions, establishes the NOC can be treated as a nuisance variable in the computation of a likelihood ratio between the prosecution and defense hypotheses, the authors show that this computation must not only use coincident models, but also coincident contextual information. The results reported here, therefore, illustrate the power of modern probabilistic systems to assess full weights-of-evidence, and to provide information on reasonable NOC ranges across multiple contexts. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2011-DN-BX-K558
                                2014-DN-BX-K026
                                2018-DU-BX-0185


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        Low-template DNA mixture interpretation: Determining the number of contributors
                                Establishing Exclusion Criteria and the Significance of Inclusion: Developing Tools for the Interpretation of Complex DNA Mixtures
                                Resolving the Forensic DNA Mixture Problem through the Development of End-to-End Single-Cell Pipelines
    
  
  
Date Published: September 1, 2021
    
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