Reproducibility of computational workflows is automated using continuous analysis.

ABSTRACT: Replication, validation and extension of experiments are crucial for scientific progress. Computational experiments are scriptable and should be easy to reproduce. However, computational analyses are designed and run in a specific computing environment, which may be difficult or impossible to match using written instructions. We report the development of continuous analysis, a workflow that enables reproducible computational analyses. Continuous analysis combines Docker, a container technology akin to virtual machines, with continuous integration, a software development technique, to automatically rerun a computational analysis whenever updates or improvements are made to source code or data. This enables researchers to reproduce results without contacting the study authors. Continuous ana

SUBMITTER: Beaulieu-Jones BK 

PROVIDER: S-EPMC6103790 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature