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

Alex Mitchell(European Bioinformatics Institute), Maxim Scheremetjew(European Bioinformatics Institute), Hubert Denise(European Bioinformatics Institute), Simon Potter(European Bioinformatics Institute), Aleksandra Tarkowska(European Bioinformatics Institute), Matloob Qureshi(European Bioinformatics Institute), Gustavo A Salazar(European Bioinformatics Institute), Sebastien Pesseat(European Bioinformatics Institute), Miguel Boland(European Bioinformatics Institute), Fiona Hunter(European Bioinformatics Institute), Petra ten Hoopen(European Bioinformatics Institute), Blaise Alako(European Bioinformatics Institute), Clara Amid(European Bioinformatics Institute), Darren J. Wilkinson(Newcastle University), Thomas P. Curtis(Newcastle University), Guy Cochrane(European Bioinformatics Institute), ROBERT FINN(European Bioinformatics Institute)
Nucleic Acids Research
October 12, 2017
Cited by 236Open Access
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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.


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