Bringing numerous methods for expression and promoter analysis to a public cloud computing service.
Where this comes from
- Record sourced from PubMed, PMID 29126246.
- Also identified by DOI 10.1093/bioinformatics/btx692 and PMC identifier 6030968.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
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. 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/. info@cyverse.warwick.ac.uk or D.L.Wild@warwick.ac.uk. Supplementary data are available at Bioinformatics online.
Medical subject headings
- Cloud Computing
- Computational Biology
- Gene Expression Regulation
- Promoter Regions, Genetic
- Software