Abstract
Cloud computing has become increasingly popular as a means of providing computational resources to ubiquitous computing tasks. Our research specifically defines computing resource needs while developing an architecture for processing and analyzing microbiome data sets. We propose a specialized cloud architecture with processing capabilities defined by various toolchains and bioinformatics scripts. This “Bioinformatics-as-a-Service” cloud architecture, named BioCloud, is in the optimization stage for processing bioinformatic requests, and allowing multi-tenant access of resources through a simple to use web-based graphical user interface. We’ll be compiling a list of Bioinformatics tools, some of which will be discussed in this paper, that will be optional components in our Biocloud platform. These tools will become apart of the plug-and-play system envisioned by the BioCloud team.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
E.E. Cloud, Available: http://eucalyptus.com/
OpenStack, Available: http://openstack.org/
OpenNebula, Available: https://opennebula.org
R. Hat, Storage for your cloud? gluster (2016). Available: https://www.gluster.org/
D. Merkel, Docker: lightweight linux containers for consistent development and deployment. Linux J. 2014(239), 2 (2014)
R. Hat, Kvm - kernel-based virtual machine (2016). Available: https://www.redhat.com/en/resources/kvm-%E2%80%93-kernel-based-virtual-machine
J.G. Caporaso, et al., QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010)
S. De, B.S. Pedersen, I.V. Yang, CruzDB: software for annotation of genomic intervals with UCSC genome-browser database. Bioinformatics 29(23), 3003–3006 (2013)
B. Langmead, C. Trapnell, M. Pop, S.L. Salzberg, Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009). https://genomebiology.biomedcentral.com/articles/10.1186/gb-2009-10-3-r25
M.C. Schatz, B. Langmead, S.L. Salzberg, Cloud computing and the dna data race. Nat. Biotechnol. 28, 691–693 (2010)
E. Plummer, J. Twin, D.M. Bulach, S.M. Garland, S. Tabrizi, A comparison of three bioinformatics pipelines for the analysis of preterm gut microbiota using 16S rRNA gene sequencing data. J. Proteomics Bioinform. 8, 283–291 (2015)
P. Schloss, et al., Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75(23), 7537–7541 (2009)
F. Meyer, D. Paarmann, M. D’Souza, R. Olson, E. Glass, et al., The metagenomics rast server - a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinform. 9, 386 (2008)
Q.D. Team, Qiita: report of progress towards an open access microbiome data analysis and visualization platform (2015)
Q. News and Announcements, Toward QIIME 2, Online (2015). Available: https://qiime.wordpress.com/2015/10/30/toward-qiime-2/
J. Nickolls, I. Buck, M. Garland, K. Skadron, Scalable parallel programming with cuda. Queue 6(2), 40–53 (2008). http://doi.acm.org/10.1145/1365490.1365500
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Staggs, C., Galloway, M. (2018). Development of a Local Cloud-Based Bioinformatics Architecture. In: Latifi, S. (eds) Information Technology - New Generations. Advances in Intelligent Systems and Computing, vol 738. Springer, Cham. https://doi.org/10.1007/978-3-319-77028-4_72
Download citation
DOI: https://doi.org/10.1007/978-3-319-77028-4_72
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77027-7
Online ISBN: 978-3-319-77028-4
eBook Packages: EngineeringEngineering (R0)