Percorrer por autor "Corre, Erwan"
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- Establishing the ELIXIR microbiome communityPublication . Finn, Robert D.; Balech, Bachir; Burgin, Josephine; Chua, Physilia; Corre, Erwan; Cox, Cymon; Donati, Claudio; Santos, Vitor Martins dos; Fosso, Bruno; Hancock, John; Heil, Katharina F.; Ishaque, Naveed; Kale, Varsha; Kunath, Benoit J.; Médigue, Claudine; Nogueira, Teresa; Pafilis, Evangelos; Pesole, Graziano; Richardson, Lorna; Santamaria, Monica; Strepis, Nikolaos; Bossche, Tim Van Den; Vizcaíno, Juan Antonio; Zafeiropoulos, Haris; Willassen, Nils P.; Pelletier, Eric; Batut, BéréniceMicrobiome research has grown substantially over the past decade in terms of the range of biomes sampled, identified taxa, and the volume of data derived from the samples. In particular, experimental approaches such as metagenomics, metabarcoding, metatranscriptomics and metaproteomics have provided profound insights into the vast, hitherto unknown, microbial biodiversity. The ELIXIR Marine Metagenomics Community, initiated amongst researchers focusing on marine microbiomes, has concentrated on promoting standards around microbiome-derived sequence analysis, as well as understanding the gaps in methods and reference databases, and identifying solutions to the computational overheads of performing such analyses. Nevertheless, the methods used and the challenges faced are not confined to marine microbiome studies, but are broadly applicable to other biomes. Thus, expanding this Marine Metagenomics Community to a more inclusive ELIXIR Microbiome Community will enable it to encompass a broader range of biomes and link expertise across ‘omics technologies. Furthermore, engaging with a large number of researchers will improve the efficiency and sustainability of bioinformatics infrastructure and resources for microbiome research (standards, data, tools, workflows, training), which will enable a deeper understanding of the function and taxonomic composition of the different microbial communities.
- metaGOflow: a workflow for the analysis of marine genomic observatories shotgun metagenomics dataPublication . Zafeiropoulos, Haris; Beracochea, Martin; Ninidakis, Stelios; Exter, Katrina; Potirakis, Antonis; De Moro, Gianluca; Richardson, Lorna; Corre, Erwan; Machado, João Paulo; Pafilis, Evangelos; Kotoulas, Georgios; Santi, Ioulia; Finn, Robert D; J. Cox, Cymon; Pavloudi, ChristinaBackground: Genomic Observatories (GOs) are sites of long-term scientific study that undertake regular assessments of the genomic biodiversity. The European Marine Omics Biodiversity Observation Network (EMO BON) is a network of GOs that conduct regular biological community samplings to generate environmental and metagenomic data of microbial communities from designated marine stations around Europe. The development of an effective workflow is essential for the analysis of the EMO BON metagenomic data in a timely and reproducible manner. Findings: Based on the established MGnify resource, we developed metaGOflow. meta GOflow supports the fast inference of taxonomic profiles from GO-derived data based on ribosomal RNA genes and their functional annotation using the raw reads. Thanks to the Research Object Crate packaging, relevant metadata about the sample under study, and the details of the bioinformatics analysis it has been subjected to, are inherited to the data product while its modular implementation allows running the workflow partially. The analysis of 2 EMO BON samples and 1 Tara Oceans sample was performed as a use case. Conclusions: metaGOflow is an efficient and robust workflow that scales to the needs of projects producing big metagenomic data such as EMO BON. It highlights how containerization technologies along with modern workflow languages and metadata package approaches can support the needs of researchers when dealing with ever-increasing volumes of biological data. Despite being initially oriented to address the needs of EMO BON, metaGOflowis a flexible and easy-to-use workflow that can be broadly used for one-sample-at-a-time analysis of shotgun metagenomics data.