An accurate and exact clustering algorithm for next generation sequencing metagenomic sequences

Abstract

Clustering algorithms are the essential tools in the target metagenomics, used to perform the taxonomic profiling of microbial communities. In the present study, an algorithmic tool called hash‐based exact alignment (HBEA) clustering algorithm is presented, which uses exact pairwise global alignment algorithm to improve the cluster quality and creates a hash table for extraction of cluster representatives. The algorithm is de novo based and uses the general de facto 97% sequence similarity score to cluster the sequences. Our experimental investigation on various types of datasets with distinct parameters and attributes showed that HBEA produces better operational taxonomic unit (OTU) clusters and computational complexity than other algorithms.