MGnify: the microbiome analysis resource in 2020

Author:

Mitchell Alex L1ORCID,Almeida Alexandre12ORCID,Beracochea Martin1ORCID,Boland Miguel1,Burgin Josephine1,Cochrane Guy1ORCID,Crusoe Michael R3,Kale Varsha1,Potter Simon C1,Richardson Lorna J1ORCID,Sakharova Ekaterina1,Scheremetjew Maxim1ORCID,Korobeynikov Anton4ORCID,Shlemov Alex4,Kunyavskaya Olga4,Lapidus Alla4,Finn Robert D1ORCID

Affiliation:

1. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK

2. Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK

3. Common Workflow Language, a project of the Software Freedom Conservancy, Inc. 137 Montague Street, Suite 380, Brooklyn, NY 11201-3548, USA

4. Center for Algorithmic Biotechnologies, Saint Petersburg State University, Russia

Abstract

Abstract MGnify (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the assembly, analysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. Over the past 2 years, MGnify (formerly EBI Metagenomics) has more than doubled the number of publicly available analysed datasets held within the resource. Recently, an updated approach to data analysis has been unveiled (version 5.0), replacing the previous single pipeline with multiple analysis pipelines that are tailored according to the input data, and that are formally described using the Common Workflow Language, enabling greater provenance, reusability, and reproducibility. MGnify's new analysis pipelines offer additional approaches for taxonomic assertions based on ribosomal internal transcribed spacer regions (ITS1/2) and expanded protein functional annotations. Biochemical pathways and systems predictions have also been added for assembled contigs. MGnify's growing focus on the assembly of metagenomic data has also seen the number of datasets it has assembled and analysed increase six-fold. The non-redundant protein database constructed from the proteins encoded by these assemblies now exceeds 1 billion sequences. Meanwhile, a newly developed contig viewer provides fine-grained visualisation of the assembled contigs and their enriched annotations.

Funder

Horizon 2020

Biotechnology and Biosciences Research Council

ELIXIR

Russian Fund for Basic Research

European Molecular Biology Laboratory

Publisher

Oxford University Press (OUP)

Subject

Genetics

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