Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.

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State: Public
Version: Final published version
Serval ID
serval:BIB_AA89A39C702D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1.
Journal
Bioinformatics
Author(s)
Pagni M., Niculita-Hirzel Hélène, Pellissier L., Dubuis A., Xenarios I., Guisan A., Sanders I.R., Goudet J., Guex N.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Publication state
Published
Issued date
2013
Peer-reviewed
Oui
Volume
29
Number
10
Pages
1268-1274
Language
english
Abstract
MOTIVATION: Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked.
RESULTS: More than 1 million hyper-variable internal transcribed spacer 1 (ITS1) sequences of fungal origin have been analyzed. The ITS1 sequences were first properly extracted from 454 reads using generalized profiles. Then, otupipe, cd-hit-454, ESPRIT-Tree and DBC454, a new algorithm presented here, were used to analyze the sequences. A numerical assay was developed to measure the reproducibility and robustness of these algorithms. DBC454 was the most robust, closely followed by ESPRIT-Tree. DBC454 features density-based hierarchical clustering, which complements the other methods by providing insights into the structure of the data.
AVAILABILITY: An executable is freely available for non-commercial users at ftp://ftp.vital-it.ch/tools/dbc454. It is designed to run under MPI on a cluster of 64-bit Linux machines running Red Hat 4.x, or on a multi-core OSX system.
CONTACT: dbc454@vital-it.ch or nicolas.guex@isb-sib.ch.
Keywords
Algorithms , Cluster Analysis , DNA, Fungal , DNA, Ribosomal Space , Fungi , Reproducibility of Results , Soil Microbiology ,
Pubmed
Web of science
Create date
18/03/2013 13:47
Last modification date
20/08/2019 15:14
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