claw-metagenomics

Metagenomic data analysis for taxonomy, resistome, and functional pathways is performed by running the metagenomics_profiler.py script on paired-end or concatenated FASTQ files to generate comprehensive profiles. This pipeline uses Kraken2, Bracken, RGI, and HUMAnN3 to produce publication-ready reports and figures.

Detecting antimicrobial resistance genes in shotgun metagenomics samples is best achieved using RGI (Resistance Gene Identifier), which identifies resistome profiles and classifies detected genes by WHO priority. This pipeline integrates RGI directly to process FASTQ files and generate standardized resistance reports.

Yes, you can use Kraken2 and Bracken for taxonomic classification of paired-end FASTQ files within this metagenomics pipeline. Kraken2 handles the initial read classification, while Bracken performs read re-estimation to provide accurate taxonomic abundance profiles.

Yes, HUMAnN3 is required for functional pathway profiling of environmental metagenomes. The pipeline optionally runs HUMAnN3 to map reads to pathway-level functional context, providing deeper insights into the metabolic and functional potential of your samples.

Reproducibility for clinical metagenomics analysis is ensured by generating a full reproducibility bundle for every run. This bundle captures the exact parameters, software versions, and reference data used, allowing you to transparently replicate your taxonomic and functional profiling results.

Processing concatenated FASTQ files instead of paired-end reads does not limit the core taxonomic and resistome profiling capabilities, but paired-end reads are standard for HUMAnN3 functional pathway analysis. The pipeline accepts both formats to accommodate different sequencing outputs.