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                            Funding & Awards
 Low-template DNA mixture interpretation: Determining the number of contributors
Award Information
Awardee
              Trustees of Boston University, BUMC
Award #
              2011-DN-BX-K558
Funding Category
              Competitive
Location
                    Boston, MA
Congressional District
              7
Status
              Closed
Funding First Awarded
              2011
Total funding (to date)
              $464,617
Original Solicitation
              NIJ FY 11 Applied Research and Development in Forensic Science for Criminal Justice Purposes
Description of original award (Fiscal Year 2011, $464,617)
The objective of this research is the development of a novel approach to interpret complex and/or low template quantities of DNA. This enhanced method to characterize complex DNA mixtures will be accompanied by the development of a complex DNA mixture interpretation tool designed to enhance traditional DNA interpretation by utilizing a likelihood ratio which makes no assumptions regarding the number of contributors or by determining the likelihood that a certain number of individuals contributed to the DNA mixture. Despite a number of commercially available tools, to obtain a likelihood ratio, the number of contributors is still qualitatively assessed by the analyst, whereby the common approach is to determine the minimum number of contributors based on the number of peaks observed at individual loci. This technique has its problems and it is the intention of this work to utilize an a posteriori probability to determine the probability that a DNA mixture is from (n) contributors. The applicant proposes to overcome these difficulties by using statistical signal processing methods to accurately infer the number of contributors to a DNA stain. Specifically, they will calculate the a posteriori probability (APP) of the number of contributors to a stain based on the genotyping results. ca/ncf



  
Grant-Funded Publications
        
                      A series of developmental validation tests for Number of Contributors platforms: Exemplars using NOCIt and a neural network
                  The A Posteriori Probability of the Number of Contributors When Conditioned on an Assumed Contributor
                  NIJ and Rutgers University: Advancing Mixture Interpretation Analysis With NOCIt
                  A large-scale validation of NOCIt's a posteriori probability of the number of contributors and its integration into forensic interpretation pipelines
                  Determining the Number of Contributors to DNA Mixtures in the Low-Template Regime Exploring the impacts of Sampling and Detection Effects
                  A Large-scale Dataset of Single and Mixed-source Short Tandem Repeat Profiles To Inform Human Identification Strategies: PROVEDIt
                  Inferring the Number of Contributors to Complex DNA Mixtures Using Three Methods: Exploring the Limits of Low-Template DNA Interpretation
                  CEESIt: A Computational Tool for the Interpretation of STR Mixtures
                  Exploring the Impacts of Ordinary Laboratory Alterations During Forensic DNA Processing on Peak Height Variation, Thresholds, and Probability of Dropout
                  Probabilistic Characterisation of Baseline Noise in STR Profiles
                  Low-Template DNA Mixture Interpretation: Determining the Number of Contributors

  
Date Created: September 15, 2011
    
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