Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database information

General information

Description: MGnify offers an automated pipeline for the analysis and archiving of microbiome data to help determine the taxonomic diversity and functional & metabolic potential of environmental samples. Users can submit their own data for analysis or freely browse all of the analysed public datasets held within the repository. In addition, users can request analysis of any appropriate dataset within the European Nucleotide Archive (ENA). User-submitted or ENA-derived datasets can also be assembled on request, prior to analysis.
Year founded: 2017
Last update:
Version: version 5.0
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: United Kingdom
Data type:
DNA
Data object:
Database category:
Major organism:
Keywords:

Contact information

University/Institution: European Bioinformatics Institute
Address:
City:
Province/State:
Country/Region: United Kingdom
Contact name (PI/Team): Robert D. Finn
Contact email (PI/Helpdesk): rdf@ebi.ac.uk

Related Database

Record metadata

Created on: 2020-06-03
Curated by:
Lina Ma [2020-06-03]

Ranking

All databases:
363/4692 (92.285%)
Gene genome and annotation:
142/1246 (88.684%)
Metadata:
28/445 (93.933%)
363
Total Rank
45
Citations
22.5
z-index

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Publications

31696235
MGnify: the microbiome analysis resource in 2020. [PMID: 31696235]
Mitchell AL, Almeida A, Beracochea M, Boland M, Burgin J, Cochrane G, Crusoe MR, Kale V, Potter SC, Richardson LJ, Sakharova E, Scheremetjew M, Korobeynikov A, Shlemov A, Kunyavskaya O, Lapidus A, Finn RD.

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.

Nucleic Acids Res. 2020:48(D1) | 3 Citations (from Europe PMC, 2020-09-12)
29069476
EBI Metagenomics in 2017: enriching the analysis of microbial communities, from sequence reads to assemblies. [PMID: 29069476]
Mitchell AL, Scheremetjew M, Denise H, Potter S, Tarkowska A, Qureshi M, Salazar GA, Pesseat S, Boland MA, Hunter FMI, Ten Hoopen P, Alako B, Amid C, Wilkinson DJ, Curtis TP, Cochrane G, Finn RD.

EBI metagenomics (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the analysis and archiving of sequence data derived from the microbial populations found in a particular environment. Over the past two years, EBI metagenomics has increased the number of datasets analysed 10-fold. In addition to increased throughput, the underlying analysis pipeline has been overhauled to include both new or updated tools and reference databases. Of particular note is a new workflow for taxonomic assignments that has been extended to include assignments based on both the large and small subunit RNA marker genes and to encompass all cellular micro-organisms. We also describe the addition of metagenomic assembly as a new analysis service. Our pilot studies have produced over 2400 assemblies from datasets in the public domain. From these assemblies, we have produced a searchable, non-redundant protein database of over 50 million sequences. To provide improved access to the data stored within the resource, we have developed a programmatic interface that provides access to the analysis results and associated sample metadata. Finally, we have integrated the results of a series of statistical analyses that provide estimations of diversity and sample comparisons.

Nucleic Acids Res. 2018:46(D1) | 42 Citations (from Europe PMC, 2020-09-12)