Abstract
The International HapMap Project is a partnership of scientists and funding agencies from different countries to develop a public resource that will help researchers find genes associated with human disease and response to pharmaceuticals. The project has collected large amounts of SNP(single-nucleotide polymorphism) data of individuals of different human populations. Many researchers have revealed evolution information from the SNP data. But how to find all the SNPs related to human evolution is still a hard work. At most time, these SNPs work together which leads to the differences between different human populations. The number of SNP combinations is very large, thus it is impossible to check all the combinations. In this paper, a novel algorithm is proposed to find the SNP combinatorial patterns whose frequencies are quite different in two different populations. The numbers of the multi-SNP combinations are regarded as the differences between each paired human populations, then a hierarchical clustering algorithm is used to construct the evolution trees for human populations. The trees from 4 chromosomes are consistent and the result can be validated by other literatures, which indicates that evolutionary information is well mined. The multi-SNP combinations found by our method can be studied further in many aspects.
This work is supported in part by the National Natural Science Foundation of China under grant NO.61232001, NO.61379108 and NO.61370172, the Program for New Century Excellent Talents in University (NCET-12-0547)
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Ding, X., Gu, H., Zhang, Z., Li, M., Wu, F. (2014). Searching SNP Combinations Related to Evolutionary Information of Human Populations on HapMap Data. In: Basu, M., Pan, Y., Wang, J. (eds) Bioinformatics Research and Applications. ISBRA 2014. Lecture Notes in Computer Science(), vol 8492. Springer, Cham. https://doi.org/10.1007/978-3-319-08171-7_25
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DOI: https://doi.org/10.1007/978-3-319-08171-7_25
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