دورية أكاديمية
Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits
العنوان: | Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits |
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المؤلفون: | Katsara, M.-A. (Maria-Alexandra), Branicki, W. (Wojciech), Pośpiech, E. (Ewelina), Hysi, P. (Pirro), Walsh, S. (Susan), Kayser, M. (Manfred), Nothnagel, M. (Michael) |
المصدر: | Forensic Science International: Genetics vol. 50 |
سنة النشر: | 2021 |
المجموعة: | RePub - Publications from Erasmus University, Rotterdam |
مصطلحات موضوعية: | Appearances, Externally visible characteristics, Forensic DNA phenotyping, Genetic prediction, Impact of priors, Predictive DNA analysis |
الوصف: | The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction pe |
نوع الوثيقة: | article in journal/newspaper |
وصف الملف: | application/pdf |
اللغة: | English |
العلاقة: | http://repub.eur.nl/pub/132099Test; urn:hdl:1765/132099 |
DOI: | 10.1016/j.fsigen.2020.102412 |
الإتاحة: | https://doi.org/10.1016/j.fsigen.2020.102412Test http://repub.eur.nl/pub/132099Test |
حقوق: | info:eu-repo/semantics/openAccess |
رقم الانضمام: | edsbas.1DDC1AB3 |
قاعدة البيانات: | BASE |
DOI: | 10.1016/j.fsigen.2020.102412 |
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