Welcome to metaGOflow’s documentation!

metaGOflow is a Common Workflow Language (CWL) based pipeline for the analysis of shotgun metagenomic data at the sample level. It was initially built to address the needs of the EMO BON community but it can be used for any type of shotgun sequencing data. metaGOflow is based on the tools and subworkflow implemented in the framework of MGnify.

It produces a Research Object Crate (RO-Crate) as its main output that includes the taxonomic inventory and/or the functional profile of the sample based on the user’s settings.

Check out the How to run metaGOflow section for further information, including Installation instructions for the project.

Note

If you find metaGOflow useful, remember to cite it:

Haris Zafeiropoulos, Martin Beracochea, Stelios Ninidakis, Katrina Exter, Antonis Potirakis, Gianluca De Moro, Lorna Richardson, Erwan Corre, João Machado, Evangelos Pafilis, Georgios Kotoulas, Ioulia Santi, Robert D Finn, Cymon J Cox, Christina Pavloudi, metaGOflow: a workflow for the analysis of marine Genomic Observatories shotgun metagenomics data, GigaScience, Volume 12, 2023, giad078, 10.1093/gigascience/giad078.

Contents

• Installation
  • Dependencies
  • Installation
• Arguments and parameters
  • Arguments
  • Parameters
  • Running metaGOflow partially
  • Example of the config.yml file
• How to run metaGOflow
  • Raw data
  • Run metaGOflow
  • Output / data products
• Description of metaGOflow’s data products
  • Quality filtering step
  • Taxonomy inventory step
  • Gene prediction step
  • Functional annotation step
  • Assembly step
  • Output example
• Frequently asked questions (FAQs)
  • Can I use metaGOflow with host-associated data?
  • Does my choice of sequencing platform affect the metaGOflow performance?
  • What is an RO-Crate and how it benefits?
  • Docker or Singularity?
  • What can I do with the metaGOflow data products?