Computational Analysis of Calcium Flux Data Using R.

Methods Mol Biol

Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire (IRIBHM), Université Libre de Bruxelles (ULB), Brussels, Belgium.

Published: October 2024

AI Article Synopsis

  • * This chapter offers a detailed guide on analyzing calcium flux data with R, featuring an example using live zebrafish imaging to illustrate important techniques like segmentation and quantification.
  • * Included is a step-by-step code example that helps researchers extract data on cell activity, analyze oscillation patterns, and create professional-quality visualizations of calcium dynamics.

Article Abstract

Calcium imaging has emerged as a powerful tool for studying cellular dynamics, with applications spanning neuroscience, cell biology, and beyond. In this chapter, we present a comprehensive guide to the computational analysis of calcium flux data using the R programming language. Using an example of in vivo live imaging of GCaMP signal in zebrafish hepatocytes, we demonstrate techniques for segmentation, normalization, and quantification of calcium transients. We provide a step-by-step code example showcasing extraction of meaningful information from calcium imaging datasets. The code allows insights into the number of oscillating cells, number of oscillations per cell within a time frame, and generation of publication-ready plots for showcasing calcium dynamics. This chapter serves as a valuable resource for researchers seeking to leverage freely available computational tools for analyzing calcium flux data at cellular resolution and uncovering novel insights into cellular physiology.

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http://dx.doi.org/10.1007/978-1-0716-4164-4_20DOI Listing

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