Tentacle: distributed quantification of genes in metagenomes

GigaScience
Fredrik BoulundErik Kristiansson

Abstract

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. 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. 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/te...Continue Reading

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Citations

Nov 29, 2016·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Viktor JonssonErik Kristiansson
Nov 27, 2018·Statistical Methods in Medical Research·Viktor JonssonErik Kristiansson
Apr 23, 2017·BMC Genomics·Tobias ÖsterlundErik Kristiansson
Apr 22, 2018·BMC Genomics·Mariana Buongermino PereiraErik Kristiansson

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Software Mentioned

pBLAT
RazerS3
FASTX
BLASTX
Illumina Genome Analyser
STORMSeq
Sun Grid Engine
FASTQ
IPython
ND

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