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We have accumulated numerous excellent software packages for analyzing large-scale biomedical data on the way to delivering on the promise of human genomics. Written as R Markdown documents, Bioconductor workflows illustrated the feasibility of organizing and demonstrating such software collections in a reproducible and human-readable way.

Going forward, how to implement fully automatic workflow execution and persistently reproducible report compilation on an industrial-scale becomes challenging from the engineering perspective. For example, the software tools across workflows usually require drastically different system dependencies and execution environments and thus need to be isolated completely.

DockFlow is a proof-of-concept project exploring the technical possibility and complexity for bioinformatics workflow containerization and orchestration using Docker. As our first experiment, all 18 available Bioconductor workflows were selected to be containerized. With the help of our R package liftr, we show it is possible to achieve the goal of persistent reproducible workflow containerization by simply creating and managing a YAML configuration file for each workflow.