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Implementation of Hierarchical Clustering using K-Mer Sparse Matrix to Analyze MERS-CoV Genetic Relationship
被引:2
|作者:
Bustamama, A.
[1
]
Ulul, E. D.
[1
]
Hura, H. F. A.
[1
]
Siswantining, T.
[1
]
机构:
[1] Univ Indonesia, Fac Math & Nat Sci FMIPA, Dept Math, Depok 16424, Indonesia
来源:
关键词:
D O I:
10.1063/1.4991246
中图分类号:
O1 [数学];
学科分类号:
0701 ;
070101 ;
摘要:
Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.
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