File:Fig2 Schulz JofPathInformatics2016 7.jpg

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Summary

Description

Figure 2. Comparison of standard application architecture and containerized architecture for clonal analysis. (a) When deployed in a virtual server, the analysis workflow was installed on CentOS 6.7 and had to be run serially due to limitations in software parallelization and local resources. Applications are launched manually in sequence to download NGS data, identify variants, and predict tumor clonality. (b) When configured in Docker containers and driven by a workflow manager, applications were automatically launched and able to scale based on available system resources. Each application was configured on its native operating system architecture within the container, as indicated in the figure.

Source

Schulz, W.L.; Durant, T.; siddon, A.J.; Torres, R. (2016). "Use of application containers and workflows for genomic data analysis". Journal of Pathology Informatics 7: 53. doi:10.4103/2153-3539.197197. 

Date

2016

Author

Schulz, W.L.; Durant, T.; siddon, A.J.; Torres, R.

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current00:35, 17 January 2017Thumbnail for version as of 00:35, 17 January 20171,210 × 342 (151 KB)Shawndouglas (talk | contribs)

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