Volume 13 Number 8 (Aug. 2018)
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JCP 2018 Vol.13(8): 905-912 ISSN: 1796-203X
doi: 10.17706/jcp.13.8.905-912

Recursive Clustering Using Different Features Sets for Metagenomic Data

Isis Bonet1, Widerman Montoya1, Andrea Mesa-Munera1, Juan Fernando Alzate2
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.

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.


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.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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