Calcium imaging enables quantitative characterization of calcium dynamics across diverse biological systems. However, measurements derived from fluorescence traces depend on analytical choices, including signal smoothing, event detection, baseline estimation, and metric definition. These analytical steps are often distributed across different software packages and can materially affect the resulting event measurements. Here we present CalciumInsights, an interactive R/Shiny application for post-processing calcium-fluorescence time series previously extracted from regions of interest (ROIs). CalciumInsights provides two complementary analysis workflows. The Fast Fourier Transform (FFT) + Baseline Analysis module supports low-frequency signal reconstruction, peak detection, baseline-dependent event quantification, and assessment of the sensitivity of metrics to alternative baseline definitions. The Wavelet Ridgewalking module provides multiscale event detection and quantification of wavelet-detected transients. Both workflows operate on tabular time-series data and provide interactive visualization and exportable event- and trace-level measurements. Using ROI-derived calcium datasets from Arabidopsis thaliana , zebrafish ( Danio rerio ), and Drosophila melanogaster , we demonstrate the application of a common trace-analysis framework across distinct organisms and imaging contexts. Comparison with published flg22 dose–response data in A. thaliana shows qualitatively consistent response trends, providing an external biological comparison without treating the published data as a ground-truth benchmark. CalciumInsights is available as an open-source online Shiny application that provides an accessible, transparent, and reproducible workflow for visualizing ROI-derived calcium traces, quantifying transient features, and evaluating how baseline and event-detection choices affect their interpretation.
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Suárez-Gómez et al. (2026) studied this question.
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