The DNA technology applied to forensic science has improved significantly in recent years. As a result of these advancements, DNA profiles can be generated from a low-template amount of DNA. This advancement, however, can lead to more complex mixtures due to the instrumentation picking up trace amounts of DNA. This leads to the need for these more challenging profiles to be interpreted. Due to the lack of standardization in DNA profile interpretation, one complex DNA profile is likely to draw several different conclusions from DNA analysts when assessing the number of contributors (NoC). Probabilistic genotyping software (PGS) is a possible solution to the problems of complex DNA profile interpretations. DNA-View® Mixture Solution™, developed by Dr. Charles Brenner, is a continuous modelling PGS that considers genotypes, peak height, stutter, dropout, and other artifacts that result from stochastic effects in the interpretation of DNA profiles. Mixture Solution has the potential to minimize some of the uncertainty inherent in DNA analysis of profiles having multiple contributors. In this project, DNA mixture analysis with Mixture Solution was applied to two and three-person mixtures having ratios ranging from 1:1 to 8:1 and 1:1:1 to 8:1:8. Two scenarios with several hypotheses were tested regarding each contributor as if they were the person of interest (POI) in a real case. Mixture Solution assigns the most favorable hypothesis for and against the POI and calculates an LR representing the comparison of those two hypotheses. In the final reports, trends previously observed in two-person mixture ratios were also observed in three-person mixtures. The main factor driving low LR assignment in three-person mixtures is low template DNA. Low peak heights and dropout are the factors driving low LR assignment. The factors that make manual DNA profile interpretation challenging can also challenge PGS. However, the robustness of Mixture Solution was demonstrated throughout the project with complex three-person mixtures.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/45583 |
| Date | 04 February 2023 |
| Creators | Juodvalkis, Joseph R. |
| Contributors | Cotton, Robin W. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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