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Streamlining Computing workflows
Latest documentation: flow-r.github.io/flowr
Flowr framework allows you to design and implement complex pipelines, and deploy them on your institution's computing cluster. This has been built keeping in mind the needs of bioinformatics workflows. However, it is easily extendable to any field where a series of steps (shell commands) are to be executed in a (work)flow.
Highlights
- No new syntax or language. Put all shell commands as a tsv file called flow mat.
- Define the flow of steps using a simple tsv file (serial, scatter, gather, burst...) called flow def.
- Works on your laptop/server or cluster (/cloud).
- Supports multiple cluster computing platforms (torque, lsf, sge, slurm ...), cloud (star cluster) OR a local machine.
- One line installation (
install.packages("flowr")) - Reproducible and transparent, with cleanly structured execution logs
- Track and re-run flows
- Lean and Portable, with easy installation
- Fine grain control over resources (CPU, memory, walltime, etc.) of each step.