Application of hierarchical clustering ordered partitioning and collapsing hybrid in Ebola Virus phylogenetic analysis

Gene clustering can be achieved through hierarchical or partition method. Both clustering methods can be combined by processing the partition and hierarchical phases alternately. This method is known as a hierarchical clustering ordered partitioning and collapsing hybrid (HOPACH) method. The Partitioning phase can be done by using PAM, SOM, or K-Means methods. The partition process is continued with the ordered process, and then it is corrected with agglomerative process, in order to have more accurate clustering results. Furthermore, the main clusters are determined by using MSS (Median Split Silhouette) value. We selected the clustering results which minimize the MSS value. In this work, we conduct the clustering on 136 Ebola Virus DNA sequences data from GenBank. The global alignment process is initially performed, followed by genetic distance calculation using Jukes-Cantor correction. In our implementation, we applied global alignment process and used the combination of HOPACH-PAM clustering using the R open source programming tool. In our results, we obtained maximum genetic distance is 0.6153407; meanwhile the minimum genetic distance is 0. Furthermore, genetic distance matrix can be used as a basis for sequences clustering and phylogenetic analysis. In our HOPACH-PAM clustering results, we obtained 10 main clusters with MSS value is 0.8873843. Ebola virus clusters can be identified by species and virus epidemic year.