MGnify is EMBL-EBI’s microbiome data and analysis resource. We provide analysis of public and pre-publication microbiome-derived sequence data that is deposited in INSDC. Our analyses cover amplicon, metagenomic, metatranscriptomic, and assembled contig data, and we also offer assembly of both short-read and long-read raw data as a service. Depending on the data being analysed, the website provides access to outputs that indicate the taxonomic diversity as well as the functional and metabolic potential of the sample. The various tools that we use to analyse the data are combined into analysis pipelines which are versioned, freely available, and fully-described using common workflow language (CWL).

MGnify also functions as an archive of the analyses we provide. You can browse and search the existing datasets by numerous parameters including biome of the sample (such as soil, human gut, marine sediment, etc), data type (amplicon, assembly, etc), and sample metadata (such as depth, temperature, disease state, etc). You can also search MGnify by protein sequence, using a HMMER-based search of our protein database, which has been generated from all of the protein predictions from all MGnify data. If you want to request analysis of a specific dataset of interest, or submit your own data for analysis, you can do so using the request options on the MGnify front page.

MGnify also provides a series of biome-specific genome catalogues which include metagenome assembled genomes (MAGs) and isolate genomes derived from samples relating to the specific biome. These genome catalogues are clustered into species-level groups, where a species-representative is then annotated with a suite of tools providing taxonomy, protein predictions, protein and RNA annotations, and more, as well as pan-genome annotations for the cluster. We provide a web-based genome browser to allow you to navigate and investigate the contents of the catalogues. You can also search against these catalogues with your own genome(s) or gene(s) of interest using the search functionalities provided in the webpages.

You can read more about our developments within MGnify in our blog posts.