Classification of the Y-haplogroup distributions of Western Eurasian populations using a self-learning algorithm |
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| Affiliation: | 1. Network of Forensic Science Institutes, Institute of Forensic Medicine, DNA Laboratory, Budapest, Hungary;2. Research Centre for Natural Sciences of the HAS, Department of Complex Systems, Budapest, Hungary;1. Immunological Research, Universy of Cartagena, Cartagena, Colombia;2. Laboratorio GENES Ltda, Medellín, Colombia;3. Instituto de Biología, Universidad de Antioquia, Medellín, Colombia;4. Laboratorio de Genética Molecular, Cruz Roja Ecuatoriana, Quito, Ecuador;5. Universidad Pontificia Bolivariana, Medellín, Colombia;6. IPATIMUP, Institute of Molecular Pathology and Immunology of the University of Porto, Portugal;1. Laboratorio de Genética Molecular de Cruz Vital – Cruz Roja Ecuatoriana Quito, Ecuador;2. Laboratorio GENES Ltda, Medellin, Colombia;1. Flinders Centre for Nanoscale Science and Technology, Flinders University, Sturt Road, Bedford Park, Adelaide, South Australia, Australia;2. School of Biological Sciences, Flinders University, Sturt Road, Bedford Park, Adelaide, South Australia, Australia |
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| Abstract: | The understanding of historical relationship between populations is a core aspect of human population history studies. We have compared the frequency of 18 different Y-SNP haplogroups in 90 Western Eurasian populations. Classification of haplogroup distribution vectors using a new self-learning classification algorithm so called “self-organizing cloud (SOC)” proved to be an effective tool to identify population groups, which share common paternal genetic features. By means of the algorithm, we have determined 10 different classes of populations based on the similarity of haplogroup composition. The analysis showed that paternal genetic markers tend to reflect geographical proximity of populations better than linguistic relationship, although certain Y-SNP haplogroups have relatively good correlation with specific language families. These observations are based on the comparative analysis of the Hg distributions of contemporary populations may reflect demographic history of them in the past. |
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| Keywords: | Y haplogroup classification Eurasian population New self-learning classification algorithm Human demographic history |
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