xySpark is a plugin for ImageJ that allows automatic detection and analysis (amplitude, width, frequency, duration and mass) of Ca2+ sparks in x-y confocal image stacks, implemented as a plugin for ImageJ/Fiji. It employs a conventional thresholding algorithm, similar to that described for use with line-scan images (e.g. Cheng et al. "Amplitude distribution of calcium sparks in confocal images: theory and studies with an automatic detection method." Biophysical Journal 76.2 (1999): 606-617; Picht et al. "SparkMaster: automated calcium spark analysis with ImageJ." American Journal of Physiology-Cell Physiology 293 (2007): C1073-C1081).
xySpark provides an interactive graphical user interface and includes methods to enable accurate identification of cells within confocal fluorescence images, compensation for slow changes in background fluorescence during data collection and options that allow exclusion of aberrant events based on spatial characteristics.
Compatibility: The plugin has been tested with versions of ImageJ 32 and 64 bit (1.48 to 1.51p) bundled with Java 1.6. It is not compatible with ImageJ versions that are bundled with Java 1.8. However, it is compatible with current versions of Fiji/ImageJ (https://fiji.sc/), including those bundled with Java 1.8. It is not compatible with ImageJ 2.0, although this is not widely used.
The plugin (provided as a .jar file) and associated files (a stack for demonstration and quick start guide with instructions for installation and use) are free to download. Place the xySpark.jar file in the 'plugins' folder of your ImageJ/Fiji installation and restart. Please read the quick start guide and instructions before attempting to use xySpark.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Please contact me directly if you wish to use xySpark on OSX or Ubuntu
We hope that xySpark will be useful to groups studying local Ca2+ regulation in muscle cells. If you wish to reference xySpark, please refer to the associated paper in Biophysical Journal which includes a detailed description of the xySpark algorithm.
Full paper: Automated Detection and Analysis of Ca2+ Sparks in x-y Image Stacks Using a Thresholding Algorithm Implemented within the Open-Source Image Analysis Platform ImageJ Biophysical Journal, 106, 566-576, 2014.
xySpark was developed by Derek S. Steele and Elliot M. Steele, University of Leeds. Funding from the British Heart Foundation and the Wellcome Trust is acknowledged.
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