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

Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., et al. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Molecular Systems Biology, 7: 539. doi:10.1038/msb.2011.75.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0017-8C09-D Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0027-C58A-C
Genre: Journal Article

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 Creators:
Sievers, F.1, Author
Wilm, A.1, Author
Dineen, D.1, Author
Gibson, T. J.1, Author
Karplus, K.1, Author
Li, W.1, Author
Lopez, R.1, Author
McWilliam, H.1, Author
Remmert, M.1, Author
Söding, J.2, Author              
Thompson, J. D.1, Author
Higgins, D. G.1, Author
Affiliations:
1external, ou_persistent22              
2Research Group of Computational Biology, MPI for Biophysical Chemistry, Max Planck Society, ou_1933286              

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Free keywords: bioinformatics hidden Markov models multiple sequence alignment
 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.

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Language(s): eng - English
 Dates: 2011-10-11
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/msb.2011.75
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Title: Molecular Systems Biology
Source Genre: Journal
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Publ. Info: London : Nature Pub. Group
Pages: - Volume / Issue: 7 Sequence Number: 539 Start / End Page: - Identifier: ISSN: 1744-4292
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000021290