¹EIA University, km 2 + 200 Vía al Aeropuerto José María Córdova, Envigado, Antioquia, Colombia.
²Centro Nacional de Secuenciación Genómica-CNSG, Facultad de Medicina, Universidad de Antioquia, Calle 67 Número 53-108, Medellín, Antioquia, Colombia.

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Abstract—Metagenomics binning process is a step prior to the taxonomic assignment of metagenomic reads of contigs, which helps to group genome sequences belonging to the same species. In this paper we propose a clustering method that is executed recursively to cluster contigs into groups of same taxa. In each step the method increases the taxonomic level, beginning with a domain and ending with a group that represents the species. The method uses a previous rule-based system to separate virus from the rest of the organism and feature selection algorithms to select different features in each step of the clustering. The clustering is based on k-means++ using Cosine and Jaccard distance, and feature selection on gain information. The proposed method outperforms classic k-means++, achieving 88.15% of purity in clusters.

Index Terms—Binning process, clustering, feature selection, metagenomics.

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Cite: Isis Bonet, Widerman Montoya, Andrea Mesa-Munera, Juan Fernando Alzate, "Recursive Clustering Using Different Features Sets for Metagenomic Data," Journal of Computers vol. 13, no. 8, pp. 905-912 , 2018.