A computational pipeline for species- and strain-level classification of metagenomic sequences - Solano, Arthur Henrique Barrios; Setubal, João Carlos (Anais do Simpósio Brasileiro de Bioinformática (BSB), 2024)
We present a pipeline for exploring genomic diversity in metagenomic datasets at the species and strain levels. To achieve accurate classifications independent of taxonomy labels, we introduce the concept of Genome Reference Set (GRS), modeled using the Maximal Independent Set problem for undirected graphs. For a given user-defined target genus, we build its GRS from GenBank genomes and use it for metagenomic contig classification using BLASTn. Additional phylogenetic processing allows the identification of putative novel species. We show that our pipeline can achieve better results than general-purpose tools, and apply the pipeline to the MetaSUB dataset, identifying two putative novel strains and one putative new species of Acinetobacter.