MAGinator enables strain-level quantification of de novo MAGs
Trine ZachariaseniD, Jakob RusseliD, Charisse PeterseniD, Gisle VestergaardiD, Shiraz Ali ShahiD, Stuart E. TurveyiD, Søren Johannes SørenseniD, Ole LundiD, Jakob StokholmiD, Asker BrejnrodiD, Jonathan ThorseniD
Abstract
MotivationMetagenomic sequencing has provided great advantages in the characterization of microbiomes, but currently available analysis tools lack the ability to combine strain-level taxonomic resolution and abundance estimation with functional profiling of assembled genomes. In order to define the microbiome and its associations with human health, improved tools are needed to enable comprehensive understanding of the microbial composition and elucidation of the phylogenetic and functional relationships between the microbes. ResultsHere, we present MAGinator, a freely available tool, tailored for the profiling of shotgun metagenomics datasets. MAGinator provides de novo identification of subspecies-level microbes and accurate abundance estimates of metagenome-assembled genomes (MAGs). MAGinator utilises the information from both gene- and contig-based methods yielding insight into both taxonomic profiles and the origin of genes as well as genetic content, used for inference of functional content of each sample by host organism. Additionally, MAGinator facilitates the reconstruction of phylogenetic relationships between the MAGs, providing a framework to identify clade-level differences within subspecies MAGs. Availability and implementationMAGinator is available as a Python module at https://github.com/Russel88/MAGinator ContactTrine Zachariasen, trine_zachariasen@hotmail.com
02 /Specification & Classification
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