In this presentation, we present NanoMGT, a tool designed to enhance marker gene typing in low-complexity mono-species samples, leveraging the unique properties of long reads. NanoMGT excels in its ability to accurately identify mutations amidst high error rates, ensuring the reliable detection of multiple strain-specific marker genes. Our tool implements a novel scoring system that rewards mutations co-occurring across different reads and penalizes densely grouped, likely erroneous variants, thereby achieving a good balance between sensitivity and precision.
A comparative evaluation of NanoMGT using a simulated multi-strain sample of seven bacterial species demonstrated superior performance relative to existing tools and the advantages of using a threshold-based filtering approach to calling minority variants in Oxford Nanopore Technologies' sequencing data.
NanoMGT's potential as a post-binning tool in metagenomic pipelines is particularly notable, enabling researchers to more accurately determine specific alleles and understand strain diversity in microbial communities.
Our findings have significant implications for clinical diagnostics, environmental microbiology, and the broader field of genomics. The findings offer a reliable and efficient approach to marker gene typing in complex metagenomic samples.
Malte Bjørn Hallgren’s presentation
