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Title |
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Protein sequence redundancy reduction: comparison of various methods |
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Authors |
Kresimir Sikic1, 2,*, Oliviero Carugo1,3 |
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Affiliation |
1Department of Structural and Computational Biology, Max F. Perutz Laboratories, Vienna University, 1030 Vienna, Austria; 2Department of Electronic Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia; 3Departement of General Chemistry, University of Pavia, I-27100 Pavia, Italy |
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+431427752208 |
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Article Type |
Hypothesis
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Date |
Received October 20, 2010; Accepted November 11, 2010; Published November 27, 2010 |
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Abstract |
Non-redundant protein datasets are of utmost importance in bioinformatics. Constructing such datasets means removing protein sequences that overreach certain similarity thresholds. Several programs such as Decrease redundancy, cd-hit, Pisces, BlastClust and SkipRedundant are available. The issue that we focus on here is to what extent the non-redundant datasets produced by different programs are similar to each other. A systematic comparison of the features and of the outputs of these programs, by using subsets of the UniProt database, was performed and is described here. The results show high level of overlap between non-redundant datasets obtained with the same program fed with the same initial dataset but different percentage of identity threshold, and moderate levels of similarity between results obtained with different programs fed with the same initial dataset and the same percentage of identity threshold. We must be aware that some differences may arise and the use of more than one computer application is advisable. |
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Keywords
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protein sequence, removing redundancy, sequence alignment. |
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Citation |
Kresimir & Oliviero, Bioinformation, 5(6): 234-239, 2010 |
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Edited by |
Martin Gollery
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ISSN |
0973-2063
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Publisher |
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License |
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
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