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greenelab / computational-reagents

Rigor, Reproducibility, Transparency, and Reagent Validity for Computational Biologists
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Continuous Analysis #5

Open linzho opened 7 years ago

linzho commented 7 years ago

I think that Continuous Analysis (thanks Brett and Casey!) is helpful, necessary, but not sufficient for reproducing computational biology experiments. It addresses issues like version control/development environment by making one researcher's computational environment easy to transfer between different researchers.

http://biorxiv.org/content/early/2016/08/11/056473

gwaybio commented 7 years ago

I think of Continuous Analysis as a strategy to implement a reproducible workflow and a framework to use reproducible tools. It uses such tools in the workflow, but I think it has rather flexible design decisions for each user (i.e. there are many tools to select from for each aspect of the workflow).

I think one of the main contributions is a re-analysis of the entire pipeline whenever something new is coded. This way the user can be aware of exactly what caused a change in the results.

Continuous analysis cannot be implemented in every scenario however as there are analysis size limits and the possibility of an analysis having unsharable data.