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                            Library & Multimedia
 The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity
NCJ Number
              254182

Author(s)
          John S. Buckleton;
                        Jo-Anne Bright;
                        Simone Gittelson;
                        Tamyra R Moretti;
                        Anthony J. Onorato;
                        Frederick R Bieber
Date Published

2019
Length
              13 pages
Annotation
              The principles behind STR mix are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights.
Abstract
              Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decisionmaking toward computer based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG ). Decisionmaking by laboratories to implement probability based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. All PG methods generate a likelihood ratio (LR ) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG , and in particular, STR mix. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STR mix, one of the available PG software. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2011-DN-BX-K541


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Test/Measurement
                                Report (Study/Research)
                                Report (Grant Sponsored)
                                Program/Project Description


  
  
        
  Award
        Population Genetic Issues for Forensic DNA Profiles
    
  
  
Date Published: January 1, 2019
    
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