EBI Metagenomics in 2017: enriching the analysis of microbial communities, from sequence reads to assemblies

Abstract 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 analy...

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Veröffentlicht in:Nucleic acids research 2018-01, Vol.46 (D1), p.D726-D735
Hauptverfasser: Mitchell, Alex L, Scheremetjew, Maxim, Denise, Hubert, Potter, Simon, Tarkowska, Aleksandra, Qureshi, Matloob, Salazar, Gustavo A, Pesseat, Sebastien, Boland, Miguel A, Hunter, Fiona M I, ten Hoopen, Petra, Alako, Blaise, Amid, Clara, Wilkinson, Darren J, Curtis, Thomas P, Cochrane, Guy, Finn, Robert D
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Sprache:eng
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Zusammenfassung:Abstract 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.
ISSN:0305-1048
1362-4962
DOI:10.1093/nar/gkx967