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. 2013 Jul 1;29(13):1685-6.
doi: 10.1093/bioinformatics/btt199. Epub 2013 Apr 28.

BioBlend: automating pipeline analyses within Galaxy and CloudMan

Clare Sloggett  1 , Nuwan Goonasekera, Enis Afgan
Affiliations

BioBlend: automating pipeline analyses within Galaxy and CloudMan

Clare Sloggett et al. Bioinformatics. .

Abstract

We present BioBlend, a unified API in a high-level language (python) that wraps the functionality of Galaxy and CloudMan APIs. BioBlend makes it easy for bioinformaticians to automate end-to-end large data analysis, from scratch, in a way that is highly accessible to collaborators, by allowing them to both provide the required infrastructure and automate complex analyses over large datasets within the familiar Galaxy environment.

Availability and implementation: http://bioblend.readthedocs.org/. Automated installation of BioBlend is available via PyPI (e.g. pip install bioblend). Alternatively, the source code is available from the GitHub repository (https://github.com/afgane/bioblend) under the MIT open source license. The library has been tested and is working on Linux, Macintosh and Windows-based systems.

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Figures

Fig. 1.
Fig. 1.
Logical structure of BioBlend library modules
See this image and copyright information in PMC

References

    1. Afgan E, et al. Galaxy CloudMan: delivering cloud compute clusters. BMC Bioinformatics. 2010;11(Suppl. 12):S4. - PMC - PubMed
    1. Afgan E, et al. Harnessing cloud computing with Galaxy Cloud. Nat. Biotech. 2011;29:972–974. - PMC - PubMed
    1. Nekrutenko A, Taylor J. Next-generation sequencing data interpretation: enhancing reproducibility and accessibility. Nat. Rev. Genet. 2012;13:667–672. - PubMed

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