Classification of the Y-haplogroup distributions of Western Eurasian populations using a self-learning algorithm

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.