https://github.com/cfrioux/metagem
An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
✓DOI references
Found 7 DOI reference(s) in README -
✓Academic publication links
Links to: biorxiv.org, zenodo.org -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (14.2%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
Repository
An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data
Basic Info
- Host: GitHub
- Owner: cfrioux
- License: mit
- Default Branch: master
- Homepage: https://franciscozorrilla.github.io/metaGEM/
- Size: 262 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Fork of franciscozorrilla/metaGEM
Created almost 5 years ago
· Last pushed almost 5 years ago
https://github.com/cfrioux/metaGEM/blob/master/
# `metaGEM`
> An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data.
[](https://www.biorxiv.org/content/10.1101/2020.12.31.424982v2.full)
[](https://travis-ci.org/franciscozorrilla/metaGEM)
[](https://github.com/franciscozorrilla/metaGEM/blob/master/LICENSE)
[](https://gitter.im/metaGEM/community)
[](https://zenodo.org/badge/latestdoi/137376259)
[](https://colab.research.google.com/drive/1I1S8AoGuJ9Oc2292vqAGTDmZcbnolbuj#scrollTo=awiAaVwSF5Fz)
`metaGEM` is a Snakemake workflow that integrates an array of existing bioinformatics and metabolic modeling tools, for the purpose of predicting metabolic interactions within bacterial communities of microbiomes. From whole metagenome shotgun datasets, metagenome assembled genomes (MAGs) are reconstructed, which are then converted into genome-scale metabolic models (GEMs) for *in silico* simulations. Additional outputs include abundance estimates, taxonomic assignment, growth rate estimation, pangenome analysis, and eukaryotic MAG identification.
## Try it now
You can set up and use `metaGEM` on the cloud by following along the google colab notebook.
[](https://colab.research.google.com/drive/1I1S8AoGuJ9Oc2292vqAGTDmZcbnolbuj#scrollTo=awiAaVwSF5Fz)
Please note that google colab does not provide the computational resources necessary to fully run `metaGEM` on a real dataset. This notebook demonstrates how to set up and use `metaGEM` by perfoming the first steps in the workflow on a toy dataset.
## Installation
You can set up `metaGEM` on your cluster with just one line of code
```
git clone https://github.com/franciscozorrilla/metaGEM.git && cd metaGEM && rm -r .git && bash env_setup.sh
```
Congratulations, you can now start using `metaGEM`. Verify your installation by using the `check` task:
```
bash metaGEM.sh --task check
```
Please consult the setup page in the wiki for further configuration instructions.
[](https://github.com/franciscozorrilla/metaGEM/wiki/Quickstart)
## Usage
Run `metaGEM` without any arguments to see usage instructions:
```
bash metaGEM.sh
```
```
Usage: bash metaGEM.sh [-t|--task TASK]
[-j|--nJobs NUMBER OF JOBS]
[-c|--cores NUMBER OF CORES]
[-m|--mem GB RAM]
[-h|--hours MAX RUNTIME]
[-l|--local]
Options:
-t, --task Specify task to complete:
SETUP
createFolders
downloadToy
organizeData
check
CORE WORKFLOW
fastp
megahit
crossMap
concoct
metabat
maxbin
binRefine
binReassemble
extractProteinBins
carveme
memote
organizeGEMs
smetana
extractDnaBins
gtdbtk
abundance
BONUS
grid
prokka
roary
eukrep
eukcc
VISUALIZATION (in development)
stats
qfilterVis
assemblyVis
binningVis
taxonomyVis
modelVis
interactionVis
growthVis
-j, --nJobs Specify number of jobs to run in parallel
-c, --nCores Specify number of cores per job
-m, --mem Specify memory in GB required for job
-h, --hours Specify number of hours to allocated to job runtime
-l, --local Run jobs on local machine for non-cluster usage
```
## Tutorial
`metaGEM` can be used to explore your own gut microbiome sequencing data from at-home-test-kit services such as [unseen bio](https://unseenbio.com/). The following tutorial showcases the `metaGEM` workflow on two unseenbio samples.
[](https://github.com/franciscozorrilla/unseenbio_metaGEM)
## Wiki
Refer to the wiki for additional usage tips, frequently asked questions, and implementation details.
[](https://github.com/franciscozorrilla/metaGEM/wiki)
## Workflow
### Core
1. Quality filter reads with [fastp](https://github.com/OpenGene/fastp)
2. Assembly with [megahit](https://github.com/voutcn/megahit)
3. Draft bin sets with [CONCOCT](https://github.com/BinPro/CONCOCT), [MaxBin2](https://sourceforge.net/projects/maxbin2/), and [MetaBAT2](https://sourceforge.net/projects/maxbin2/)
4. Refine & reassemble bins with [metaWRAP](https://github.com/bxlab/metaWRAP)
5. Taxonomic assignment with [GTDB-tk](https://github.com/Ecogenomics/GTDBTk)
6. Relative abundances with [bwa](https://github.com/lh3/bwa) and [samtools](https://github.com/samtools/samtools)
7. Reconstruct & evaluate genome-scale metabolic models with [CarveMe](https://github.com/cdanielmachado/carveme) and [memote](https://github.com/opencobra/memote)
8. Species metabolic coupling analysis with [SMETANA](https://github.com/cdanielmachado/smetana)
### Bonus
9. Growth rate estimation with [GRiD](https://github.com/ohlab/GRiD), [SMEG](https://github.com/ohlab/SMEG) or [CoPTR](https://github.com/tyjo/coptr)
10. Pangenome analysis with [roary](https://github.com/sanger-pathogens/Roary)
11. Eukaryotic draft bins with [EukRep](https://github.com/patrickwest/EukRep) and [EukCC](https://github.com/Finn-Lab/EukCC)
## Active Development
If you want to see any new additional or alternative tools incorporated into the `metaGEM` workflow please raise an issue or create a pull request. Snakemake allows workflows to be very flexible, so adding new rules is as easy as filling out the following template and adding it to the Snakefile:
```
rule package-name:
input:
rules.rulename.output
output:
f'{config["path"]["root"]}/{config["folder"]["X"]}/{{IDs}}/output.file'
message:
"""
Helpful and descriptive message detailing goal of this rule/package.
"""
shell:
"""
# Well documented command line instructions go here
# Load conda environment
set +u;source activate {config[envs][package]};set -u;
# Run tool
package-name -i {input} -o {output}
"""
```
## Publications
The `metaGEM` workflow was used in the following publication(s):
```
Plastic-degrading potential across the global microbiome correlates with recent pollution trends
Jan Zrimec, Mariia Kokina, Sara Jonasson, Francisco Zorrilla, Aleksej Zelezniak
bioRxiv 2020.12.13.422558; doi: https://doi.org/10.1101/2020.12.13.422558
```
[](https://www.biorxiv.org/content/10.1101/2020.12.13.422558v2.full)
## Please cite
```
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
```
[](https://www.biorxiv.org/content/10.1101/2020.12.31.424982v2.full)
## Contact
Please reach out with any comments, concerns, or discussions regarding `metaGEM`.
[](https://gitter.im/metaGEM/community)
[](https://twitter.com/metagenomez)
[](https://www.linkedin.com/in/fzorrilla94/)
[](fz274@cam.ac.uk)
Owner
- Name: Clémence Frioux
- Login: cfrioux
- Kind: user
- Location: Bordeaux
- Company: Inria
- Website: https://cfrioux.github.io/
- Twitter: c_frioux
- Repositories: 21
- Profile: https://github.com/cfrioux
Researcher - Bioinformatician