# MetaQuad: shared informative variants discovery in metagenomic samples

## TL;DR

MetaQuad is a computational tool that efficiently identifies shared genetic variants in metagenomic data, helping to study microbial evolution and antibiotic resistance.

## Contribution

MetaQuad introduces a novel density-based clustering approach to reduce false positives in SNP discovery from metagenomic samples.

## Key findings

- MetaQuad significantly reduces false positive SNPs without affecting true positive rates.
- It detected 7591 variants across 529 antibiotic resistance genes in H. pylori patients.
- Nucleotide diversity increased in some genes 6 weeks after antibiotic treatment.

## Abstract

Strain-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.

MetaQuad utilizes a density-based clustering technique to effectively distinguish between shared variants and 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 7591 variants across 529 antibiotic resistance genes. The nucleotide diversity of some genes is increased 6 weeks after antibiotic treatment, potentially indicating the role of these genes in specific antibiotic treatments.

MetaQuad is an open-source Python package available via https://github.com/holab-hku/MetaQuad.