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Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis.


ABSTRACT: A key aspect of neuroscience research is the development of powerful, general-purpose data analyses that process large datasets. Unfortunately, modern data analyses have a hidden dependence upon complex computing infrastructure (e.g., software and hardware), which acts as an unaddressed deterrent to analysis users. Although existing analyses are increasingly shared as open-source software, the infrastructure and knowledge needed to deploy these analyses efficiently still pose significant barriers to use. In this work, we develop Neuroscience Cloud Analysis As a Service (NeuroCAAS): a fully automated open-source analysis platform offering automatic infrastructure reproducibility for any data analysis. We show how NeuroCAAS supports the design of simpler, more powerful data analyses and that many popular data analysis tools offered through NeuroCAAS outperform counterparts on typical infrastructure. Pairing rigorous infrastructure management with cloud resources, NeuroCAAS dramatically accelerates the dissemination and use of new data analyses for neuroscientific discovery.

SUBMITTER: Abe T 

PROVIDER: S-EPMC9464703 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis.

Abe Taiga T   Kinsella Ian I   Saxena Shreya S   Buchanan E Kelly EK   Couto Joao J   Briggs John J   Kitt Sian Lee SL   Glassman Ryan R   Zhou John J   Paninski Liam L   Cunningham John P JP  

Neuron 20220722 17


A key aspect of neuroscience research is the development of powerful, general-purpose data analyses that process large datasets. Unfortunately, modern data analyses have a hidden dependence upon complex computing infrastructure (e.g., software and hardware), which acts as an unaddressed deterrent to analysis users. Although existing analyses are increasingly shared as open-source software, the infrastructure and knowledge needed to deploy these analyses efficiently still pose significant barrier  ...[more]

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