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Data released on March 02, 2017

Example use case of SIC with the ndmg pipeline (SIC:ndmg)

Kiar, G; Gorgolewski, K, J; Kleissas, D; Gray Roncal, W; Litt, B; Poldrack, R, A; Wandell, B; Wiener, M; Vogelstein, R, J; Burns, R; Vogelstein, J, T (2017): Example use case of SIC with the ndmg pipeline (SIC:ndmg) GigaScience Database. http://dx.doi.org/10.5524/100285 RIS BibTeX Text

Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools which drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called ''science in the cloud'' (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results which will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended. We introduce and document an example use case of SIC with the ndmg pipeline, thus entitled SIC:ndmg. We have developed a capability which enables users to launch a cloud instance and run a container which performs an analysis of a cohort of structural and diffusion magnetic resonance imaging scans by (i) downloading the required data from a public repository in the cloud, (ii) fully processing each subject's data to estimate a connectome for each subject's associated graph statistics, and, optionally, (iii) plot quality control figures of various multivariate graph statistics.

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Additional information:

https://github.com/neurodata/sic

https://github.com/neurodata/ndmg/

http://scienceinthe.cloud

Software

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ReadmeTEXT2.32 KB2017-02-28
GitHub archivezip1.36 MB2017-03-01
GitHub archivearchive5.29 MB2017-02-28
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