The main content of this article presents PatternJ, a novel toolset for ImageJ/Fiji that allows for the automated and quantitative analysis of regular spatial patterns found in various biological samples.
The key highlights and insights are:
PatternJ provides a user-friendly graphical interface that guides the user through the analysis process, including manual selection of regions of interest, setting pattern characteristics, automated feature extraction, and comprehensive analysis.
The tool can extract the position of individual pattern features, such as bands, blocks, and actin staining, with subpixel precision, even in images with low signal-to-noise ratio. This enables detailed quantification of pattern organization and variability.
PatternJ was validated on simulated data with varying signal-to-noise ratios, intensity variations, and periodicity, demonstrating its robustness in handling challenging biological images.
The tool was successfully applied to analyze regular patterns in a variety of biological samples, including sarcomeres in cardiomyocytes and insect muscles, actin rings in neurons, and somites in zebrafish embryos, using different imaging techniques such as confocal microscopy, STORM, and electron microscopy.
Compared to existing tools, PatternJ stands out for its user-friendliness, ability to extract complex pattern features, and provision of comprehensive analysis outputs, including distributions of pattern parameters and an averaged pattern image, without requiring programming skills.
Overall, PatternJ provides a valuable and accessible solution for biologists to quantify regular spatial patterns in their samples, enabling more detailed and reproducible analyses that can accelerate discoveries in various fields.
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by Baheux Blin,... at www.biorxiv.org 01-20-2024
https://www.biorxiv.org/content/10.1101/2024.01.17.576053v1Deeper Inquiries