Installing Plugins

Synapse's core provides data I/O, table operations, and display nodes. Domain-specific functionality — image analysis, statistics, plotting, segmentation — is delivered through plugins.

How to Install

From the App

1. Go to Plugins > Install Plugin
2. Select a plugin file (.py, .zip, or .synpkg)
3. Click Plugins > Reload Plugins

New nodes will appear in the Node Explorer tree under their respective categories.

Manual Installation

Copy plugin files into your platform's plugin directory:

Platform	Path
macOS	~/Library/Application Support/Synapse/plugins/
Windows	%APPDATA%\Synapse\plugins\
Linux	~/.config/Synapse/plugins/
From source	./plugins/ (next to synapse/)

Managing Plugins

• Plugins > Plugin Manager lets you enable, disable, or uninstall plugins
• Disabled plugins are not loaded on startup but remain on disk
• Plugin settings persist across updates

Available Plugins

Image Analysis

Comprehensive image processing toolkit powered by scikit-image. Includes color conversion, exposure adjustment, filters (Gaussian, median, Frangi, etc.), morphological operations, thresholding, segmentation, distance transforms, particle measurements, ROI drawing, and more.

~70 nodes covering the full image analysis pipeline.

Statistical Analysis

Descriptive statistics, normality tests, group comparisons (t-test, Mann-Whitney, Kruskal-Wallis), two-way ANOVA, linear and nonlinear regression, contingency analysis, survival analysis (Kaplan-Meier, Cox), and PCA.

13 nodes for statistical testing and modeling.

Figure Plotting

Publication-ready figures with matplotlib and seaborn. Scatter, box, violin, swarm, bar, histogram, KDE, XY line, heatmap, volcano, regression, and survival plots. All plots are configurable with palettes, axis labels, and styling options.

16 nodes for data visualization.

SAM2 & Cellpose

This plugin package includes three sets of nodes:

• SAM2 Segmentation — interactive segmentation using Meta's Segment Anything Model 2. Click on objects to segment them, manage multiple objects, and run automatic full-image segmentation.
• Cellpose — deep learning cell and nucleus segmentation (cyto, cyto2, cyto3, nuclei models). Supports single image and batch folder processing.
• Video & Tracking — video frame extraction (imageio + ffmpeg), multi-object tracking via centroid re-prompting, trajectory analysis, and track filtering.

All run on ONNX Runtime (no PyTorch). Models auto-download on first use.

3D Volume

Volume rendering and analysis for 3D microscopy data. Requires pyqtgraph.

Cheminformatics

RDKit-based chemistry nodes for molecule editing, similarity search, molecular docking (AutoDock Vina), protein preparation, and structure visualization. All dependencies are vendored — no external installs needed.

Filopodia Analysis

Specialized nodes for detecting and measuring cell protrusions (filopodia) from skeleton-based analysis.

Packaging Your Own Plugin

See Creating Plugins for how to build and package custom nodes. Use package_plugin.py to create .synpkg packages for distribution.