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

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          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.

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          QIIME allows analysis of high-throughput community sequencing data.

          J. Gregory Caporaso, Justin Kuczynski, Jesse Stombaugh … (2010)
          Article 0 comments Cited 5848 times – based on 0 reviews     Review now
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            Search and clustering orders of magnitude faster than BLAST.

            Robert Edgar (2010)
            Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
            Article 0 comments Cited 3434 times – based on 0 reviews     Review now
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              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              Patrick Schloss, Sarah Westcott, Thomas Ryabin … (2009)
              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
              Article 0 comments Cited 2976 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (publisher-id): nar
                Journal ID (hwp): nar
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): January 2013
                Publication date (Electronic): 27 November 2012
                Publication date PMC-release: 27 November 2012
                Volume: 41
                Issue: Database issue , Database issue
                Pages: D590-D596
                Affiliations
                1Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, 2Jacobs University Bremen gGmbH, School of Engineering and Science, D-28759 Bremen and 3Ribocon GmbH, D-28359 Bremen, Germany
                Author notes
                *To whom correspondence should be addressed. Tel: +49 421 2028970; Fax: +49 421 2028580; Email: fog@ 123456mpi-bremen.de

                The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

                Article
                Publisher ID: gks1219
                DOI: 10.1093/nar/gks1219
                PMC ID: 3531112
                PubMed ID: 23193283
                SO-VID: 85a54951-8797-4f5d-ad4d-c4702cb95d0d
                Copyright © © The Author(s) 2012. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.

                History
                Date received : 14 September 2012
                Date revision received : 26 October 2012
                Date accepted : 31 October 2012
                Page count
                Pages: 7
                Categories
                Subject: Articles

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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