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metaGEM is a Snakemake-based workflow designed to generate high quality metagenome assembled genomes from short read paired-end data, reconstruct genome scale metabolic models, and perform community metabolic interaction simulations on high performance computing clusters. In the metaGEM manuscript we apply the workflow to lab culture, human gut, plant associated, bulk soil, and TARA oceans metagenomic samples.
The fastest way for you to start submitting jobs with metaGEM is to follow this quickstart guide. If you want to have more control over the software installed you can alternatively follow this manual setup guide.
A detailed tutorial of the metaGEM core workflow is demonstrated here.
You can find answers to FAQs here.
The image below shows a modified version of the workflow diagram, highlighting the most important parts of the core workflow on the left-hand column and auxiliary or supplementary tools on the right-hand column.

In the following pages you can find documentation regarding the implementation of each tool within the Snakefile. For a more hands on demonstration of how to use metaGEM please see the tutorial above.
- Quality filter reads with fastp
- Assembly with megahit
- Draft bin sets with CONCOCT, MaxBin2, and MetaBAT2
- Refine & reassemble bins with metaWRAP
- Taxonomic assignment with GTDB-tk
- Relative abundances with bwa
- Reconstruct & evaluate genome-scale metabolic models with CarveMe and memote
- Species metabolic coupling analysis with SMETANA

While the metaGEM publication is currently in the second round of revision please cite the pre-print if you use our pipeline in your research:
metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
Francisco Zorrilla, Kiran R. Patil, Aleksej Zelezniak
bioRxiv 2020.12.31.424982; doi: https://doi.org/10.1101/2020.12.31.424982
- Quality filter reads with fastp
- Assembly with megahit
- Draft bin sets with CONCOCT, MaxBin2, and MetaBAT2
- Refine & reassemble bins with metaWRAP
- Taxonomic assignment with GTDB-tk
- Relative abundances with bwa
- Reconstruct & evaluate genome-scale metabolic models with CarveMe and memote
- Species metabolic coupling analysis with SMETANA