Spyke Viewer and the cloud: quick algorithm development and large scale data analysis for electrophysiology
Effective analysis of the increasingly large amounts of data generated by current electrophysiological experiments and simulations requires powerful new tools. Spyke Viewer (Pröpper and Obermayer, 2013) is an open source, multi-platform application for navigating, visualizing and analyzing such data.
Based on Python and the Neo framework (Garcia et al., 2014), Spyke Viewer supports reading and writing a wide variety of file formats. The loaded Neo object hierarchy is represented in a graphical object browser. Together with user-defined filters, the object browser is used to select data for visualization and analysis.
Operations on the selected data can be performed using an integrated Python console or with plugins. Spyke Viewer includes a number of plugins for common plots and basic analyses. Users can easily create their own plugins using the integrated Python editor or external tools. Plugins are implemented as Python classes and can use any existing library.
Spyke Viewer now supports executing plugins on computing or cloud servers using Celery [1]. Plugins, even with local code changes, can be submitted for remote execution with a single command. An arbitrary number of compute nodes can be used and new nodes can be added during runtime. Spyke Viewer includes a remote execution manager where users can manage queued, running and finished plugins or view parameters, progress and results. This allows quick iteration during development and simple execution even for large scale analyses.
[1] http://www.celeryproject.org/
References
(Garcia et al., 2014) Garcia, S., et al. "Neo: an object model for handling electrophysiology data in multiple formats." Frontiers in Neuroinformatics 8 (2014).
(Pröpper and Obermayer, 2013) Pröpper, Robert, and Klaus Obermayer. "Spyke Viewer: a flexible and extensible platform for electrophysiological data analysis." Frontiers in Neuroinformatics 7 (2013).
Keywords:
Electrophysiology,
data sharing,
algorithm development,
algorithm sharing,
Neo,
visualization,
cloud
Conference:
Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014.
Presentation Type:
Demo, not to be considered for oral presentation
Topic:
Electrophysiology
Citation:
Pröpper
R
(2014). Spyke Viewer and the cloud: quick algorithm development and large scale data analysis for electrophysiology.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2014.
doi: 10.3389/conf.fninf.2014.18.00047
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Received:
22 Apr 2014;
Published Online:
04 Jun 2014.
*
Correspondence:
Mr. Robert Pröpper, TU Berlin, Berlin, Germany, robert.proepper@gmail.com