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bioRxiv · 10.1101/2023.10.09.561628

MetaQuad: Shared Informative Variants Discovery in Metagenomic Samples

XU, S.·Morgan, D.·Qian, G.·Huang, Y.·Ho, J. W. K.
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Abstract

MotivationStrain-level analysis of metagenomic data has garnered significant interest in recent years. Microbial single nucleotide polymorphisms (SNPs) are genomic variants that can reflect strain-level differences within a microbial species. The diversity and emergence of SNPs in microbial genomes may reveal evolutionary history and environmental adaptation in microbial populations. However, efficient discovery of shared polymorphic variants in a large collection metagenomic samples remains a computational challenge. ResultsMetaQuad employs a density-based clustering technique to efficiently differentiate shared variants from non-polymorphic sites using shotgun metagenomic data. Empirical comparisons with other state-of-the-art methods show that MetaQuad significantly reduces the number of false-positive SNPs without greatly affecting the true-positive rate. We used MetaQuad to identify antibiotic-associated variants in patients who underwent Helicobacter pylori eradication therapy. MetaQuad detected 7,591 variants across 529 antibiotic resistance genes. The nucleotide diversity of some genes is increased six weeks after antibiotic treatment, potentially indicating the role of these genes in specific antibiotic treatments. AvailabilityMetaQuad is an open-source Python package available via https://github.com/holab-hku/MetaQuad. Contactjwkho@hku.hk Supplementary informationSupplementary data are available at XXXX online.

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XU, S., Morgan, D., Qian, G., Huang, Y., Ho, J. W. K.. 2023-10-10. MetaQuad: Shared Informative Variants Discovery in Metagenomic Samples. https://doi.org/10.1101/2023.10.09.561628

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