Alignment-free Methods for Classification of Metagenomic Data

Abstract

Metagenomics studies microbial communities by analyzing their genomic content directly sequenced from the environment. In this contribution, alignment-free methods based on word frequency will be introduced. It has been proven, that these methods are effective in processing of short metagenomic sequence reads produced by Next-Generation Sequencing technologies. To evaluate the potential of word frequency based methods, the k-mer analysis was applied on simulated dataset of metagenomic sequence reads with length of 600 nucleotides. Then the data were enrolled for a hierarchical cluster analysis. Results have shown that the proposed method is able to cluster genome fragments of the same taxa.