This repository contains a Docker recipe for the construction of BioWorkbench, a high-performance framework for managing and analyzing bioinformatics experiments.
Each experiment comprises a set of activities to be executed in a chained way, also known as workflows. Thus, they were modeled and defined using the Swift, a scientific workflow management system that allows them to run in high-performance computing environments.
The Docker recipe contains all the programs and configurations required to run the following workflows:
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SwiftGecko: https://github.com/mmondelli/swift-gecko
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SwiftPhylo: https://github.com/mmondelli/swift-phylo
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RASflow: https://github.com/mmondelli/rasflow
Please refer to the links above for a better description of each of the experiments, as well as instructions for their execution.
To build an image from the Dockerfile you can run (assuming you are inside the directory where the file is located):
docker build -t bioworkbench:latest .
To run a container for this image, you can run:
docker run --rm -p 3837:3838 --name bio bioworkbench:latest
And with this you can access a web interface to analyze the provenance of the workflows executed through the address: http://localhost:3837/workbench
This interface provides a menu where it is necessary to inform which workflow will be analyzed (Script name). When choosing a date range (Date range), the field below (Script ID) will list all the identifiers of each execution of this workflow performed during the reported period. The user must then choose one of these options and click on the Update button. The analyses presented on the right side will be updated according to the chosen workflow execution.
To run the experiments and other commands in the running container, you can use (from another terminal):
docker exec -ti bio /bin/bash
This Dockerfile is also configured for automatic build in this Docker hub repository. Thus, you can use the pull command to get the BioWorkbench image:
docker pull malumondelli/bioworkbench