SICT: automated detection and supervised inspection of fast Ca2+ transients

Roberta Mancini; Tobias van der Bijl; Quentin Bourgeois-Jaarsma; Rizky Lasabuda; Alexander J. Groffen

doi:10.1038/s41598-018-33847-4

SICT: automated detection and supervised inspection of fast Ca²⁺ transients

Roberta Mancini, Tobias van der Bijl, Quentin Bourgeois-Jaarsma, Rizky Lasabuda, Alexander J. Groffen

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Recent advances in live Ca2+ imaging with increasing spatial and temporal resolution offer unprecedented opportunities, but also generate an unmet need for data processing. Here we developed SICT, a MATLAB program that automatically identifies rapid Ca2+ rises in time-lapse movies with low signal-to-noise ratios, using fluorescent indicators. A graphical user interface allows visual inspection of automatically detected events, reducing manual labour to less than 10% while maintaining quality control. The detection performance was tested using synthetic data with various signal-to-noise ratios. The event inspection phase was evaluated by four human observers. Reliability of the method was demonstrated in a direct comparison between manual and SICT-aided analysis. As a test case in cultured neurons, SICT detected an increase in frequency and duration of spontaneous Ca2+ transients in the presence of caffeine. This new method speeds up the analysis of elementary Ca2+ transients.

Original language	English
Article number	15523
Pages (from-to)	1-13
Number of pages	13
Journal	Scientific Reports
Volume	8
DOIs	https://doi.org/10.1038/s41598-018-33847-4
Publication status	Published - 19 Oct 2018

Funding

We thank Robbert Zalm, Jurjen Broeke, Desiree Schut, Frank den Oudsten and Joost Hoetjes for excellent technical assistance and Matthijs Verhage for critically reading the manuscript. This research was funded by the Netherlands Organization for Health Research and Development (ZonMW project 91113022).

Funders	Funder number
Netherlands Organization for Health Research and Development
ZonMw	91113022

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10.1038/s41598-018-33847-4

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Cite this

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abstract = "Recent advances in live Ca2+ imaging with increasing spatial and temporal resolution offer unprecedented opportunities, but also generate an unmet need for data processing. Here we developed SICT, a MATLAB program that automatically identifies rapid Ca2+ rises in time-lapse movies with low signal-to-noise ratios, using fluorescent indicators. A graphical user interface allows visual inspection of automatically detected events, reducing manual labour to less than 10\% while maintaining quality control. The detection performance was tested using synthetic data with various signal-to-noise ratios. The event inspection phase was evaluated by four human observers. Reliability of the method was demonstrated in a direct comparison between manual and SICT-aided analysis. As a test case in cultured neurons, SICT detected an increase in frequency and duration of spontaneous Ca2+ transients in the presence of caffeine. This new method speeds up the analysis of elementary Ca2+ transients.",

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AU - Groffen, Alexander J.

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