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Journal Article

The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

MPS-Authors
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Quast,  C.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Pruesse,  E.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Yilmaz,  P.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Gerken,  J.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Schweer,  T.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Yarza,  P.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Peplies,  J.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Glöckner,  F. O.
Microbial Genomics Group, Department of Molecular Ecology, Max Planck Institute for Marine Microbiology, Max Planck Society;

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Citation

Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., et al. (2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research (London), 41(D1), D590-D596.


Cite as: https://hdl.handle.net/21.11116/0000-0001-C74C-A
Abstract
SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.