Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega

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Title: Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega
Authors: Sievers, Fabian
Wilm, Andreas
Dineen, David
Higgins, D. (Des)
et al.
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Date: 11-Oct-2011
Abstract: Multiple sequence alignments are fundamental to many sequence analysis methods. Most alignments are computed using the progressive alignment heuristic. These methods are starting to become a bottleneck in some analysis pipelines when faced with data sets of the size of many thousands of sequences. Some methods allow computation of larger data sets while sacrificing quality, and others produce high-quality alignments, but scale badly with the number of sequences. In this paper, we describe a new program called Clustal Omega, which can align virtually any number of protein sequences quickly and that delivers accurate alignments. The accuracy of the package on smaller test cases is similar to that of the high-quality aligners. On larger data sets, Clustal Omega outperforms other packages in terms of execution time and quality. Clustal Omega also has powerful features for adding sequences to and exploiting information in existing alignments, making use of the vast amount of precomputed information in public databases like Pfam.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: EMBO Press
Journal: Molecular Systems Biology
Volume: 7
Issue: 539
Start page: 1
End page: 6
Copyright (published version): 2011 EMBO and Macmillan Publishers Limited
Keywords: BioinformaticsHidden Markov modelsMultiple sequence alignment
DOI: 10.1038/msb.2011.75
Language: en
Status of Item: Peer reviewed
Appears in Collections:Conway Institute Research Collection
Medicine Research Collection

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