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Nat Commun. 2018 Mar 5;9(1):940. doi: 10.1038/s41467-018-03297-7.

A browser-based tool for visualization and analysis of diffusion MRI data.

Author information

1
Institute for Learning & Brain Sciences, University of Washington, Portage Bay Building, Box 357988, Seattle, WA, 98195, USA. jyeatman@uw.edu.
2
Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, 98195, USA. jyeatman@uw.edu.
3
Department of Physics, University of Washington, Seattle, WA, 98195, USA.
4
Department of Chemical Engineering, University of Washington, Seattle, WA, 98195, USA.
5
Institute for Learning & Brain Sciences, University of Washington, Portage Bay Building, Box 357988, Seattle, WA, 98195, USA.
6
Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, 98195, USA.
7
eScience Institute, WRF Data Science Studio, University of Washington, Physics/Astronomy Tower (PAT), 6th Floor 3910 15th Ave NE, Seattle, WA, 98195, USA.
8
eScience Institute, WRF Data Science Studio, University of Washington, Physics/Astronomy Tower (PAT), 6th Floor 3910 15th Ave NE, Seattle, WA, 98195, USA. arokem@gmail.com.

Abstract

Human neuroscience research faces several challenges with regards to reproducibility. While scientists are generally aware that data sharing is important, it is not always clear how to share data in a manner that allows other labs to understand and reproduce published findings. Here we report a new open source tool, AFQ-Browser, that builds an interactive website as a companion to a diffusion MRI study. Because AFQ-Browser is portable-it runs in any web-browser-it can facilitate transparency and data sharing. Moreover, by leveraging new web-visualization technologies to create linked views between different dimensions of the dataset (anatomy, diffusion metrics, subject metadata), AFQ-Browser facilitates exploratory data analysis, fueling new discoveries based on previously published datasets. In an era where Big Data is playing an increasingly prominent role in scientific discovery, so will browser-based tools for exploring high-dimensional datasets, communicating scientific discoveries, aggregating data across labs, and publishing data alongside manuscripts.

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