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. 2007;35(21):7188-96.
doi: 10.1093/nar/gkm864. Epub 2007 Oct 18.

SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB

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SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB

Elmar Pruesse et al. Nucleic Acids Res. 2007.

Abstract

Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs.

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Figures

Figure 1.
Figure 1.
Sequence length distribution of rRNA genes in the SILVA 91 SSU database. The dotted line represents the sequence distribution directly after importing, the solid line after quality checks and alignment. The huge amount of sequences around 100 bases reflect the first impact of tag sequencing approaches.
Figure 2.
Figure 2.
Sequence length distribution in the SILVA 91 LSU database. The dotted line represents the sequence distribution directly after importing, the solid line after quality checks and alignment. The huge amount of sequences around 100 bases reflect the first impact of tag sequencing approaches.

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