doepipeline: a systematic approach to optimizing multi-level and multi-step data processing workflows.
Daniel SvenssonRickard SjögrenDavid SundellAndreas SjödinJohan TryggPublished in: BMC bioinformatics (2019)
Our proposed methodology provides a systematic and robust framework for optimizing software parameter settings, in contrast to labor- and time-intensive manual parameter tweaking. Implementation in doepipeline makes our methodology accessible and user-friendly, and allows for automatic optimization of tools in a wide range of cases. The source code of doepipeline is available at https://github.com/clicumu/doepipeline and it can be installed through conda-forge.