Afanc: a Metagenomics Tool for Variant Level Disambiguation of NGS Datasets

Abstract

Genomics is amongst the most powerful tools available for mounting a clinical response to infectious disease. The accurate and precise taxonomic evaluation of pathogens is essential when building a picture of pathogenicity, virulence, transmission, and drug resistance. Carrying out such profiling in a high throughput manner necessitates the development of reliable bioinformatic tools. Here we present Afanc, a novel metagenomic profiler which is sensitive down to species and strain level taxa, and capable of elucidating the complex pathogen profile of compound datasets. We compared Afanc against currently available cutting edge profilers using 3 datasets: single species read sets simulated from the full Mycobacteriaceae taxonomic landscape; compound read sets containing multiple Mycobacteriaceae species and variants; and real data covering the majority of the M. tuberculosis lineage taxonomic space. Afanc outperformed all profilers, both generic and Mycobacteriaceae specific, across all tested fields. As a species agnostic profiler, we predict that Afanc will be of great utility when carrying out highly specific and sensitive pathogen profiling of clinical datasets. Such analyses are essential in advising both the clinical response to an individual disease case, and in forming the foundation of epidemiological surveys.