metagenomix 2.5.0

metagenomix is a pipeline of pipelines to conduct metagenomic analyses on Slurm/Torque

metagenomix

metagenomix is a pipeline creator, monitor and manager that takes care of writing the command-lines for any shotgun metagenomics software, either as bash scripts or Slurm / Torque jobs (incl. scratch space usage), based on user-defined configurations for databases, co-assemblies, strain foci, as well as software-specific or computing resource parameters (incl. memory, scratch relocations, modules and conda environments).

Outputs are scripts that the user needs to run sequentially, which typically can be handled by packages such as snakemake: this is not (yet) used here as metagenomix is only meant to facilitate the creation, monitoring, management and access of shotgun metagenomic analyses results for personalized pipelines including any software.

Any software? Well, if not already in the softwares list, someone will need to add it to metagenomix, following the instructions to contribute code.

Please read the documentation using the Wiki pages

Installation

pip install metagenomix

or

pip install --upgrade git+https://github.com/FranckLejzerowicz/metagenomix.git

Depencencies

While a container solution with all the softwares and conda environments is being develop, it currently is the responsibility of the user to install all the databases and softwares that the pipeline will allow you to prepare command-lines for. Some softwares necessitate to be present either as a single binary file or with an entire folder (e.g., pre-trained models or scripts). Since some softwares require the user to edit configurations after install, some level of manual installation/tuning will be needed before usage.

Usage

Usage: metagenomix [OPTIONS] COMMAND [ARGS]...

  Metagenomix command line manager

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.

Commands:
  create   Write jobs for your pipeline configuration.
  export   Prepare an archive for specific pipeline outputs.
  manage   Edit the contents of your pipeline output folder.
  monitor  Check IO/job status of your pipeline configuration.
  merge    Combine the per-sample outputs into feature tables.

Detailed explanations for each command at Running Wiki page