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Francisco Zorrilla edited this page Jan 30, 2023 · 42 revisions

What is metaGEM?

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 paper we apply the workflow to lab culture, human gut, plant associated, bulk soil, and TARA oceans metagenomic samples.

Quickstart

The fastest way for you to start submitting jobs with metaGEM is to follow this updated setup guide. Alternatively, you may have a look at the older quickstart guide or the manual setup guide.

Tutorial

A detailed tutorial of the metaGEM core workflow is demonstrated here.

Frequently asked questions

You can find answers to FAQs here.

Workflow

The workflow below is adapted from Figure 1 of the metaGEM manuscript:

metawrapfigs_v2 002

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.

Core

  1. Quality filter reads with fastp
  2. Assembly with megahit
  3. Draft bin sets with CONCOCT, MaxBin2, and MetaBAT2
  4. Refine & reassemble bins with metaWRAP
  5. Taxonomic assignment with GTDB-tk
  6. Relative abundances with bwa
  7. Reconstruct & evaluate genome-scale metabolic models with CarveMe and memote
  8. Species metabolic coupling analysis with SMETANA

Bonus

  1. Growth rate estimation
  2. Pangenome analysis based on MAGs
  3. Eukaryotic draft bins with EukRep and EukCC

Binning performance

The following image is adapted from supplementary figure 2 of the metaGEM manuscript, highlighting the advantage of using the bin refinement and reassembly technique. It can also serve as somewhat anecdotal yet quantitative comparison of binning tool performances:

image

Please cite

metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
Francisco Zorrilla, Filip Buric, Kiran R Patil, Aleksej Zelezniak
Nucleic Acids Research, 2021; gkab815, https://doi.org/10.1093/nar/gkab815