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

Pagni, Marco ; Niculita-Hirzel, Hélène ; Pellissier, Loïc ; Dubuis, Anne ; Xenarios, Ioannis ; Guisan, Antoine ; Sanders, Ian R. ; Goudet, Jérôme ; Guex, Nicolas

In: Bioinformatics, 2013, vol. 29, no. 10, p. 1268-1274

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    Titre
    • Density-based hierarchical clustering of pyro-sequences on a large scale—the case of fungal ITS1
    Auteur
    • Pagni, Marco. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Niculita-Hirzel, Hélène. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Pellissier, Loïc. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Dubuis, Anne. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Xenarios, Ioannis. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Guisan, Antoine. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Sanders, Ian R.. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Goudet, Jérôme. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    • Guex, Nicolas. Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland, Occupational Environment Department, Institute for Work and Health, Universities of Lausanne and Geneva, 1066 Lausanne, Switzerland and Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland
    Type de document
    • Postprint
    Identifiant OAI-PMH
    • oai:doc.rero.ch:290773
    Summary
    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