Prediction of Eye Color from Genetic Data Using Bayesian Approach*
Correction(s) for this article
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Erratum
- Volume 58Issue 2Journal of Forensic Sciences
- pages: 565-565
- First Published online: March 12, 2013
Ewelina Pośpiech M.S.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Search for more papers by this authorJolanta Draus-Barini M.S.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Search for more papers by this authorTomasz Kupiec Ph.D.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Search for more papers by this authorAnna Wojas-Pelc Ph.D., M.D.
Department of Dermatology, Collegium Medicum of the Jagiellonian University, Skawińska 8, 31-066 Kraków, Poland.
Search for more papers by this authorWojciech Branicki Ph.D.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Department of Genetics and Evolution, Institute of Zoology, Jagiellonian University, Ingardena 6, 30-060 Kraków, Poland.
Search for more papers by this authorEwelina Pośpiech M.S.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Search for more papers by this authorJolanta Draus-Barini M.S.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Search for more papers by this authorTomasz Kupiec Ph.D.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Search for more papers by this authorAnna Wojas-Pelc Ph.D., M.D.
Department of Dermatology, Collegium Medicum of the Jagiellonian University, Skawińska 8, 31-066 Kraków, Poland.
Search for more papers by this authorWojciech Branicki Ph.D.
Section of Forensic Genetics, Institute of Forensic Research, Westerplatte 9, 31-033 Kraków, Poland.
Department of Genetics and Evolution, Institute of Zoology, Jagiellonian University, Ingardena 6, 30-060 Kraków, Poland.
Search for more papers by this authorSupported by a grant from the Ministry of Science and Higher Education in Poland, No. ON301115136 (science fund for years 2009–2012).
Abstract
Abstract: Prediction of visible traits from genetic data in certain forensic cases may provide important information that can speed up the process of investigation. Research that has been conducted on the genetics of pigmentation has revealed polymorphisms that explain a significant proportion of the variation observed in human iris color. Here, on the basis of genetic data for the six most relevant eye color predictors, two alternative Bayesian network model variants were developed and evaluated for their accuracy in prediction of eye color. The first model assumed eye color to be categorized into blue, brown, green, and hazel, while the second variant assumed a simplified classification with two states: light and dark. It was found that particularly high accuracy was obtained for the second model, and this proved that reliable differentiation between light and dark irises is possible based on analysis of six single nucleotide polymorphisms and a Bayesian procedure of evidence interpretation.
Supporting Information
Table S1. PCR primer sequences.
Table S2. Extension primer sequences.
Table S3. Conditional probability table used in BN-I model variant calculated from the frequency of each pair of alleles for each SNP in four eye color groups: blue, green, hazel and brown.
Table S4. Conditional probability table used in BN-II model variant calculated from the frequency of each pair of alleles for each SNP in two eye-color groups: light and dark.
Table S5. Testing results for BN-I and BN-II model variants for eighty external samples.
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| JFO_2077_sm_TableS1-S5.doc683 KB | Supporting info item |
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