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. 2016 Jan 4;44(D1):D595-603.
doi: 10.1093/nar/gkv1195. Epub 2015 Nov 17.

EBI metagenomics in 2016--an expanding and evolving resource for the analysis and archiving of metagenomic data

Alex Mitchell  1 , Francois Bucchini  1 , Guy Cochrane  1 , Hubert Denise  1 , Petra ten Hoopen  1 , Matthew Fraser  1 , Sebastien Pesseat  1 , Simon Potter  1 , Maxim Scheremetjew  1 , Peter Sterk  1 , Robert D Finn  2
Affiliations

EBI metagenomics in 2016--an expanding and evolving resource for the analysis and archiving of metagenomic data

Alex Mitchell et al. Nucleic Acids Res. .

Abstract

EBI metagenomics (https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and archiving of metagenomic and metatranscriptomic data. Over the last 2 years, the resource has undergone rapid growth, with an increase of over five-fold in the number of processed samples and consequently represents one of the largest resources of analysed shotgun metagenomes. Here, we report the status of the resource in 2016 and give an overview of new developments. In particular, we describe updates to data content, a complete overhaul of the analysis pipeline, streamlining of data presentation via the website and the development of a new web based tool to compare functional analyses of sequence runs within a study. We also highlight two of the higher profile projects that have been analysed using the resource in the last year: the oceanographic projects Ocean Sampling Day and Tara Oceans.

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Figures

Figure 1.
Figure 1.
Schematic of the analysis pipeline. Processes/components are indicated as circles and inputs/outputs are represented by rectangles. The structure of pipeline v2.0 is similar to that of v1.0. Following input file preparation and a QC stage (to remove short/low quality reads), the pipeline branches into two parts: one performing taxonomic classification (based on 16S rRNA) and the other providing functional annotation (based on pCDS matches to a subset of the InterPro databases). A full description of the steps, tools and reference libraries used is provided on the EMG website at https://www.ebi.ac.uk/metagenomics/pipelines/2.0.
Figure 2.
Figure 2.
EMG analysis pipeline throughput for the Tara Oceans project, based on analyses completed each month. With relatively static compute resources available, the upward trend is a result of pipeline improvements. The highest value gives an indication of our current expected peak processing capacity.
Figure 3.
Figure 3.
Biome icons and search-by-biome functionality. (A) Biomes for projects are indicated by icons on the EMG website. The numbers under the icons represent the number of projects belonging to each biome. (B) The biome filter allows users to select a biome of interest (for example marine) and returns matching projects.
Figure 4.
Figure 4.
Examples of different data visualizations available via the online comparison tool. The high level GO terms assigned to runs within a project can be compared to each other via bar charts, stacked columns, PCA plots and heatmaps.
Figure 5.
Figure 5.
Analysis summary files at the project level are available to download in TSV format. In this example, pCDS matching InterPro entries (rows) for all runs in a project (columns) are provided.
See this image and copyright information in PMC

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