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Tentacle: distributed quantification of genes in metagenomes

Journal article
Authors Fredrik Boulund
Anders Sjögren
Erik Kristiansson
Published in GigaScience
Volume 4
Pages artikel nr 40
ISSN 2047-217X
Publication year 2015
Published at Department of Mathematical Sciences, Mathematical Statistics
Pages artikel nr 40
Language en
Links http://dx.doi.org/10.1186/s13742-0...
https://gup.ub.gu.se/file/178406
Keywords Distributed computing, Master-worker, Next-generation sequencing, Metagenomics, Gene quantification, DNA sequence analysis, Read mapping, DNA sequencing
Subject categories Bioinformatics (Computational Biology)

Abstract

Background In metagenomics, microbial communities are sequenced at increasingly high resolution, generating datasets with billions of DNA fragments. Novel methods that can efficiently process the growing volumes of sequence data are necessary for the accurate analysis and interpretation of existing and upcoming metagenomes. Findings Here we present Tentacle, which is a novel framework that uses distributed computational resources for gene quantification in metagenomes. Tentacle is implemented using a dynamic master-worker approach in which DNA fragments are streamed via a network and processed in parallel on worker nodes. Tentacle is modular, extensible, and comes with support for six commonly used sequence aligners. It is easy to adapt Tentacle to different applications in metagenomics and easy to integrate into existing workflows. Conclusions Evaluations show that Tentacle scales very well with increasing computing resources. We illustrate the versatility of Tentacle on three different use cases. Tentacle is written for Linux in Python 2.7 and is published as open source under the GNU General Public License (v3). Documentation, tutorials, installation instructions, and the source code are freely available online at: http://bioinformatics.math.chalmers.se/tentacle.

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