First steps into the cloud: Using Amazon data storage and computing with Python notebooks

With the oncoming age of big data, biologists are encountering more use cases for cloud-based computing to streamline data processing and storage. Unfortunately, cloud platforms are difficult to learn, and there are few resources for biologists to demystify them. We have developed a guide for experi...

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Bibliographic Details
Published in:	PloS one 2023-02, Vol.18 (2), p.e0278316-e0278316
Main Authors:	Pollak, Daniel J, Chawla, Gautam, Andreev, Andrey, Prober, David A
Format:	Article
Language:	eng
Subjects:	Animals Big Data Biologists Budgets Calcium imaging Cloud Computing Coding Collaboration Computer and Information Sciences Computer industry Costs Data processing Data storage Information Storage and Retrieval Lab Protocol Management Neural coding Neuroimaging People and Places Personal computers Physical Sciences Programming Languages Protocol Reproducibility Research and Analysis Methods Science Policy Social Sciences Software Web services Work stations Zebrafish
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Summary:	With the oncoming age of big data, biologists are encountering more use cases for cloud-based computing to streamline data processing and storage. Unfortunately, cloud platforms are difficult to learn, and there are few resources for biologists to demystify them. We have developed a guide for experimental biologists to set up cloud processing on Amazon Web Services to cheaply outsource data processing and storage. Here we provide a guide for setting up a computing environment in the cloud and showcase examples of using Python and Julia programming languages. We present example calcium imaging data in the zebrafish brain and corresponding analysis using suite2p software. Tools for budget and user management are further discussed in the attached protocol. Using this guide, researchers with limited coding experience can get started with cloud-based computing or move existing coding infrastructure into the cloud environment.
ISSN:	1932-6203 1932-6203