The Department of

Statistics and Operations Research

University of North Carolina at Chapel Hill

Ph.D. Defense

Thursday May 11th, 2023

1pm

Location: Hanes 125

or Zoom: https://unc.zoom.us/j/99892878701

Taylor Petty

Under the direction of Jan Hannig (UNC) and Hariharan Iyer (National Institute of Standards and Technology)

Bayesian Forensic DNA Mixture Deconvolution With a Novel String Similarity Measure

Forensic scientists have great interest in deconvolving profiles in crime scene samples, particularly to test the presence of a courtroom suspect. However, DNA degradation, low material quantity, and mixed signals from multiple contributors are near-ubiquitous challenges. Additionally, crime scene analysis includes the polymerase chain reaction (PCR) for amplification, but this generates artifact sequences that confound the true allelic signal. Forensic scientists worldwide currently use capillary electrophoresis, a length-based sequencing method, but the advent of massively parallel sequencing technology enables data analysis at a much higher resolution, increasing the ability to discriminate between profiles in the sample. This more advanced data type requires new statistical methods to ensure rigorous analysis. In this work we propose a Bayes factor, computed by Markov chain Monte Carlo, that tests whether a person of interest’s DNA was present at a crime scene. The model is able to include known contributors, such as the victim. As part of this methodology, a novel string edit distance was published to measure similarity between alleles and their artifacts generated by PCR. This edit distance accommodates “stutter,” a common artifact seen specifically after PCR of forensic markers. In various simulation studies, the Bayes factor estimates produced by the model demonstrate ability to detect the suspect in a mixture of contributors, with variability in the estimate as a function of the suspect’s mixing proportions. When testing a suspect not present, the result is decisive rejection exonerating the suspect.

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