Optimization and validation of HIrisPlex-S system used in skin color estimation
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Abstract (EN)
Forensic DNA phenotyping (FDP), the prediction of a person's visible characteristics from DNA, has become a rapidly growing subfield in forensic genetics. FDP can assist police investigations in the search for unknown perpetrators who often cannot be identified through standard DNA profiling. Therefore, The IrisPlex, which predicts eye color, and the HIrisPlex systems, which predicts eye and hair color together, were developed by Walsh et al. Chaitanya et al. HIrisplex-S system, developed by and the most comprehensive pigmentation prediction system so far; includes 41 SNP regions, 17 of which are skin color, allowing hair, eye, and skin color to be predicted simultaneously. It predicts phenotype probabilities in skin 5 color categories. In this study, the optimization and validation of the HIrisPlex-S system (17 skin color-related SNP loci) was performed and the success of skin color prediction was tested on 26 volunteers. The HIrisPlex-S online web tool was used for skin color estimation. In the validation of the study, the analysis threshold was determined 239 RFU, and the sensitivity limit was determined 0,125 ng. The same genotypes were obtained through repeatability studies. The accuracy of the HIrisPlex-S system, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. The result showed that the method predicted pale skin color with %73,08 accuracy, intermediate skin color with %78,8 accuracy, and dark to black skin color with %100 accuracy. The Very pale and dark skin color phenotypes were not obtained from the genotypes of volunteer individuals, so no predictions were made in these categories. For the HIrisPlex-S system to be used in criminal cases, more samples from the Turkish population should be studied.
Author
Rümeysa Vatansever
Institution
How to Cite
Rümeysa Vatansever (Master Thesis). Optimization and validation of HIrisPlex-S system used in skin color estimation, 2024, İstanbul University-Cerrahpaşa.
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