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  Indian J Med Microbiol
 

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

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