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NIJ and Rutgers University: Advancing Mixture Interpretation Analysis With NOCIt

NCJ Number
255479
Date Published
Author(s)
National Institute of Justice
Agencies
NIJ-Sponsored
Annotation
This brief describes the methodology and findings of research funded by the National Institute of Justice and conducted at Rutgers University by Drs. Catherine Grgicak and Desmong Lun regarding the analysis of DNA samples that contain at least two contributors.
Abstract
Using forensic probabilistic tools to identify a DNA sample’s number of contributors (NOC) is crucial to an accurate computation of the weight of evidence for a person of interest. Traditionally, calculating the NOC for a forensic short tandem repeat (STR) DNA profile involves evaluating peaks per locus and dividing by two, ratios of alleles, allelic balance at a locus, and review to ensure all loci fit the estimated NOC; however, this method provides only an estimate about the minimum NOC that could explain the mixture rather than the probability of a certain NOC; and there can be variation between analysts, which introduces subjectivity when using this method to determine NOC. The Rutgers research developed and validated a probabilistic system called “NOCIt,” which determines a probability distribution on the NOC given an STR electropherogram. NOCIt incorporates models of peak height, forward and reverse stutter, and noise and allelic drop-out, in addition to accounting for the number of alleles, so it is considered a fully continuous system. NOCIt trial licenses and all mixture data are available free to the forensic community for implementation and validation purposes.
Date Created: September 30, 2020