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Welcome to the documentation of FooDMe

CI License GitHub release (latest by date) DOI Snakemake

FooDMe is a reproducible and scalable snakemake workflow for the analysis of DNA metabarcoding experiments, with a special focus on food and feed samples.

Tip

FooDMe2 is a complete re-write of FooDMe with improved capabilities and portability. You can try it out and give your feedback using the link above.

Support for FooDMe will continue until FooDMe2 reaches enough maturity for a stable release.


Overview

FooDMe processes paired-end Illumina reads in the following way:

  • Primer trimming
  • Quality filtering
  • Sequence clustering based on identity clustering (OTUs), dereplication, or denoising (ASVs)
  • Similarity-search cluster sequences in a user-provided database
  • Determine a taxonomic consensus for each cluster sequence
  • Outputs quality reports and results in human-readable formats


Citation

If you use FooDMe for research please cite us!

The source code is deposited on Zenodo and citable using the DOI at the top of this page (Last release)

We also published a benchmarking study for 16S Metabarcoding of meat products:

Denay, G.; Preckel, L.; Petersen, H.; Pietsch, K.; Wöhlke, A.; Brünen-Nieweler, C. Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding. Foods 2023, 12, 968. https://doi.org/10.3390/foods12050968


Connex tools

BaRCoD: A snakemake workflow aiming at recovering and analyzing barcodes for metabarcoding experiments. Using a set of primers, finds possible amplicon in the database (or a taxonomic subset thereof) and performs pairwise alignements of barcodes. Available from Github.

TaxidTools: A Python library to load, process and work with taxonomy definitions. Documentation on the homepage.


About us

FooDMe is developed by Grégoire Denay at the Chemical and Veterinary Investigation Office Rhein-Ruhr-Wupper, an official public laboratory in the field of consumer health protection.

More about CVUA-RRW.