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#FAIRness Friday: A new series spotlighting researchers who are investing effort in making their work Findable, Accessible, Interoperable and Reusable
For this inaugural edition, we’re showcasing the work of Bo Li ( @BigGoodBo) and his team, who recently published a new #opensource #transcriptomic analysis framework, Cumulus, that aims to standardize and scale up #singlecell and #singlenucleus analysis. https://doi.org/10.1038/s41592-020-0905-x
As @BigGoodBo explains in his recent post on our blog, some key goals for Cumulus were to make the tools accessible to a wide audience and to support reproducibility in computational research. https://support.terra.bio/hc/en-us/articles/360047598811-Making-large-scale-RNASeq-analysis-scalable-and-cost-effective-with-Cumulus
To that end, the Cumulus team developed a public workspace in @TerraBioApp featuring example data, preconfigured workflows and jupyter notebooks that reproduce key parts of the analyses described in their paper. https://app.terra.bio/#workspaces/kco-tech/Cumulus
The Cumulus team also made a series of short tutorial videos that explain how to use the workspace, to enable other researchers to try out the tools and test the methodologies for themselves with minimal effort.
You can learn more about Cumulus from @BigGoodBo himself in this excellent thread: https://twitter.com/biggoodbo/status/1290366819811954688
In closing, we applaud the efforts of @BigGoodBo and the Cumulus team to make their tools and methods #FAIR for the #singlecell research community!
