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Bioinformatics. 2017 Oct 15;33(20):3292-3295. doi: 10.1093/bioinformatics/btx394.

EDEN: evolutionary dynamics within environments.

Münch PC1,2,3, Stecher B2,4, McHardy AC1,3,5,6.

Author information

1
Computational Biology of Infection Research, Helmholtz Centre for Infection Research, 38124 Brunswick, Germany.
2
Max von Pettenkofer-Institute for Hygiene and Clinical Microbiology, Ludwig-Maximilian University of Munich, 80336 Munich, Germany.
3
German Centre for Infection Research (DZIF), Partner Site Hanover-Brunswick, 38124 Brunswick, Germany.
4
DZIF, Partner Site LMU Munich, 80336 Munich, Germany.
5
Department of Algorithmic Bioinformatics.
6
Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University Dusseldorf, 40225 Dusseldorf, Germany.

Abstract

Summary:

Metagenomics revolutionized the field of microbial ecology, giving access to Gb-sized datasets of microbial communities under natural conditions. This enables fine-grained analyses of the functions of community members, studies of their association with phenotypes and environments, as well as of their microevolution and adaptation to changing environmental conditions. However, phylogenetic methods for studying adaptation and evolutionary dynamics are not able to cope with big data. EDEN is the first software for the rapid detection of protein families and regions under positive selection, as well as their associated biological processes, from meta- and pangenome data. It provides an interactive result visualization for detailed comparative analyses.

Availability and implementation:

EDEN is available as a Docker installation under the GPL 3.0 license, allowing its use on common operating systems, at http://www.github.com/hzi-bifo/eden.

Contact:

alice.mchardy@helmholtz-hzi.de.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
28637301
PMCID:
PMC5860032
DOI:
10.1093/bioinformatics/btx394
[Indexed for MEDLINE]
Free PMC Article

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