This paper reports on a method, NOCIt, that calculates the a posteriori probability on the number of contributors to a forensic sample, while taking into account signal peak heights, population allele frequencies, baseline noise, allele dropout, and stutter.
This paper reports on a project that addressed the problematic nature of DNA profiles generated from short tandem repeats (STRs) because of dropout, allele overlap, and artifacts such as stutter. The researchers' goal was to develop computational methods for the analysis of STR profiles that were robust to those phenomena and that used quantitative peak height information captured in profiles. In the first part of the research, the authors characterized the distribution of signal, noise, and stutter peak heights, and studied their dependence on template DNA amount. For the second part of the project, the paper reports on the authors' development of a method to identify the number of contributors to a DNA sample. The method, NOCIt, calculates the a posteriori probability on the number of contributors to a forensic sample. In the third and final part of their research, the authors developed a computational tool, MatchIt, to directly compute a continuous Likelihood Ratio (LR) for a person of interest, treating other contributors that might exist as interference.
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