Browsing by Subject "Forensic DNA phenotyping"

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    Evaluation of supervised machine-learning methods for predicting appearance traits from DNA
    (Elsevier, 2021) Katsara, Maria-Alexandra; Branicki, Wojciech; Walsh, Susan; Kayser, Manfred; Nothnagel, Michael; VISAGE Consortium; Biology, School of Science
    The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have already been established using multinomial logistic regression (MLR), the prediction performances of other possible classification methods have not been thoroughly investigated thus far. Motivated by the question to identify a potential classifier that outperforms these specific trait models, we conducted a systematic comparison between the widely used MLR and three popular machine learning (ML) classifiers, namely support vector machines (SVM), random forest (RF) and artificial neural networks (ANN), that have shown good performance outside EVC prediction. As examples, we used eye, hair and skin color categories as phenotypes and genotypes based on the previously established IrisPlex, HIrisPlex, and HIrisPlex-S DNA markers. We compared and assessed the performances of each of the four methods, complemented by detailed hyperparameter tuning that was applied to some of the methods in order to maximize their performance. Overall, we observed that all four classification methods showed rather similar performance, with no method being substantially superior to the others for any of the traits, although performances varied slightly across the different traits and more so across the trait categories. Hence, based on our findings, none of the ML methods applied here provide any advantage on appearance prediction, at least when it comes to the categorical pigmentation traits and the selected DNA markers used here.
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    Exploring the association between SNPs and facial morphology in a Spanish population
    (Springer Nature, 2025-04-22) Navarro-López, Belén; Wilke, Franziska; Suárez-Ulloa, Victoria; Baeta, Miriam; Martos-Fernández, Rubén; Moreno-López, Olatz; Olalde, Iñigo; Martínez-Jarreta, Begoña; Jiménez, Susana; Walsh, Susan; de Pancorbo, Marian M.; Medical and Molecular Genetics, School of Medicine
    Understanding and predicting human external phenotypes, particularly facial shape, is of great value for individual identification. However, facial morphology is a highly complex trait. Despite its complexity, recent genome wide association studies (GWAS) have shed light on potential SNPs associated with facial features, offering a first glimpse into the likely genetic background of individual appearance. In this paper we have selected a set of 116 candidate SNPs and studied their association with facial phenotypes in a Spanish population of 412 individuals, highlighting a wide spectrum of facial morphologies worthy of investigation. We performed canonical correlation analysis (CCA) between each SNP and the observed spacial variation in facial shape, from its representation by a dense mesh of 7160 quasi-landmarks, revealing significant associations within different facial segments. In particular, ten SNPs are highlighted for their strong association within this Spanish population, some of them uncovering correlations with novel facial regions. These findings underline the importance and usefulness of conducting candidate SNP studies, not only to validate existing associations but also to unveil novel correlations within subpopulations.