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Updated: Feb 19, 2026

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae
Published on: April 25, 2015
Bringing numerous methods for expression and promoter analysis to a public cloud computing service
Krzysztof Polanski1, Bo Gao1, Sam A Mason2
1Department of Statistics.
Summary:
Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project.
Availability And Implementation:
The integrated apps can be found at http://www.cyverse.org/discovery-environment, while the raw code is available at https://github.com/cyversewarwick and the corresponding Docker images are housed at https://hub.docker.com/r/cyversewarwick/.
Contact:
info@cyverse.warwick.ac.uk or D.L.Wild@warwick.ac.uk.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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