MGnify: the microbiome analysis resource in 2020

Alex L. Mitchell, Alexandre Almeida, Martin Beracochea, Miguel Boland, Josephine Burgin, Guy Cochrane, Michael R. Crusoe, Varsha Kale, Simon C. Potter, Lorna J. Richardson, Ekaterina Sakharova, Maxim Scheremetjew, Anton Korobeynikov, Alex Shlemov, Olga Kunyavskaya, Alla Lapidus, Robert D. Finn

Результат исследований: Научные публикации в периодических изданияхстатья

Выдержка

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.

Язык оригиналаанглийский
Страницы (с-по)D570-D578
Число страниц9
ЖурналNucleic Acids Research
Том48
Номер выпускаD1
Ранняя дата в режиме онлайн7 ноя 2019
DOI
СостояниеОпубликовано - 8 янв 2020

Отпечаток

Metagenomics
Microbiota
Molecular Sequence Annotation
Protein Databases
Workflow
Language
Population
Proteins
Datasets

Предметные области Scopus

  • Генетика

Цитировать

Mitchell, A. L., Almeida, A., Beracochea, M., Boland, M., Burgin, J., Cochrane, G., ... Finn, R. D. (2020). MGnify: the microbiome analysis resource in 2020. Nucleic Acids Research, 48(D1), D570-D578. https://doi.org/10.1093/nar/gkz1035
Mitchell, Alex L. ; Almeida, Alexandre ; Beracochea, Martin ; Boland, Miguel ; Burgin, Josephine ; Cochrane, Guy ; Crusoe, Michael R. ; Kale, Varsha ; Potter, Simon C. ; Richardson, Lorna J. ; Sakharova, Ekaterina ; Scheremetjew, Maxim ; Korobeynikov, Anton ; Shlemov, Alex ; Kunyavskaya, Olga ; Lapidus, Alla ; Finn, Robert D. / MGnify : the microbiome analysis resource in 2020. В: Nucleic Acids Research. 2020 ; Том 48, № D1. стр. D570-D578.
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abstract = "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.",
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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 2020, 'MGnify: the microbiome analysis resource in 2020', Nucleic Acids Research, том. 48, № D1, стр. D570-D578. https://doi.org/10.1093/nar/gkz1035

MGnify : the microbiome analysis resource in 2020. / Mitchell, Alex L.; Almeida, Alexandre; Beracochea, Martin; Boland, Miguel; Burgin, Josephine; Cochrane, Guy; Crusoe, Michael R.; Kale, Varsha; Potter, Simon C.; Richardson, Lorna J.; Sakharova, Ekaterina; Scheremetjew, Maxim; Korobeynikov, Anton; Shlemov, Alex; Kunyavskaya, Olga; Lapidus, Alla; Finn, Robert D.

В: Nucleic Acids Research, Том 48, № D1, 08.01.2020, стр. D570-D578.

Результат исследований: Научные публикации в периодических изданияхстатья

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AU - Mitchell, Alex L.

AU - Almeida, Alexandre

AU - Beracochea, Martin

AU - Boland, Miguel

AU - Burgin, Josephine

AU - Cochrane, Guy

AU - Crusoe, Michael R.

AU - Kale, Varsha

AU - Potter, Simon C.

AU - Richardson, Lorna J.

AU - Sakharova, Ekaterina

AU - Scheremetjew, Maxim

AU - Korobeynikov, Anton

AU - Shlemov, Alex

AU - Kunyavskaya, Olga

AU - Lapidus, Alla

AU - Finn, Robert D.

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Mitchell AL, Almeida A, Beracochea M, Boland M, Burgin J, Cochrane G и соавт. MGnify: the microbiome analysis resource in 2020. Nucleic Acids Research. 2020 Янв. 8;48(D1):D570-D578. https://doi.org/10.1093/nar/gkz1035