Hello,

I am currently engaged in a metagenome analysis project, focusing on antimicrobial resistance (AMR) in water samples. My approach involves DNA sequencing using the ONT nanopore, followed by alignment with the kma tool against the ResFinder database (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2336-6). This helps me identify the sets of AMR genes present before and after treatment.

Included in my data is a ConClave score for each gene, which reflects the combined alignment quality for each template. Although my study does not involve differential expression analysis and lacks raw RNAseq data, I've come across suggestions that DESeq2 might still be applicable for my analysis.

My goal is to determine whether there is a noticeable improvement in water quality in terms of AMR gene presence after treatment. Can DESeq2 be effectively used in this context to analyze the data, even though it's traditionally used for RNAseq data?

Thank you for your insights.

I've heard that metagenomics is not distributionally compatible with the modeling assumptions in DESeq2. But I don't know much about alternative workflows.

Maybe check the software here:

https://statdivlab.github.io/