--- id: pycat-napari version: "1.6.458" license: License ------- BSD 3-Clause License Copyright (c) 2024, Christian Neureuter, Banerjee Lab, State University of New York at Buffalo All rights reserved. Redistribution and use in source and binary… (full text in the JSON record) license_treatment: permissive maintenance: active --- # pycat-napari — Python Condensate Analysis Toolbox - A napari-based tool for biomolecular condensate analysis License: permissive · Maintenance: active · Downloads: 297.0K/mo ## What it is and what it does PyCAT-Napari is a low/no-code desktop application for analyzing biomolecular condensates in microscopy images. Built on napari, it provides a graphical interface to segment condensates, measure their properties (area, intensity, shape, texture), perform colocalization analysis, track trajectories over time, and estimate biophysical parameters like saturation concentration and diffusion rates. It handles 2D single images, Z-stacks, and time-series acquisitions in both fluorescence and brightfield modalities. The package bundles 28 runtime dependencies—including numpy, scipy, scikit-image, torch, cellpose, and PyQt5—to deliver image processing, machine-learning-based segmentation, statistical analysis, and a full GUI. It is designed for researchers without programming experience, offering batch processing via JSON configuration and specialized pipelines for cellular condensates, in-vitro droplets, time-series analysis, and fibril structures. Optional GPU acceleration is available for Cellpose segmentation and morphological operations. Use it for: - Segment and measure fluorescent biomolecular condensates in fixed or live-cell images without writing code. - Analyze colocalization between two or more fluorescent channels using object-based and pixel-wise metrics. - Track condensate trajectories over time and measure fusion kinetics, diffusion, and coarsening mechanisms. - Estimate saturation concentration (C_sat) from intensity distributions and dilution-series experiments. - Process large time-series or Z-stack acquisitions in batch mode by recording GUI actions and replaying them across a folder. - Measure morphological complexity (fractal dimension, lacunarity) and spatial organization (DBSCAN clustering, Voronoi) of condensate ensembles. ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. PyCAT-Napari is a napari-based desktop application for detecting, measuring, and analyzing biomolecular condensates in fluorescence and brightfield microscopy images, with support for 2D, Z-stack, and time-series data. Yes, if you are a biologist or microscopist analyzing condensates and want a low-code GUI tool. The package is actively maintained, permissively licensed, has no known vulnerabilities, and offers a comprehensive feature set tailored to condensate research. Install friction is low for a pure-Python package, though the 28 dependencies mean a dedicated environment is prudent. Not suitable if you need Python 3.11 or earlier, or if you prefer a command-line or programmatic API over a GUI. ## Install pip install pycat-napari uv add pycat-napari poetry add pycat-napari ## Installing pycat-napari Before you install: Low friction: pure Python wheel with no compiled dependencies beyond its runtime stack. Active maintenance with a release 8 days ago. However, 28 runtime dependencies including torch, cellpose, and PyQt5 mean installation time and disk footprint are substantial; plan for a dedicated environment. License in practice: BSD 3-Clause permissive license. You may use, modify, and distribute the software freely provided you retain copyright notices and disclaimers. No restrictions on commercial use. Quickstart: pip install pycat-napari python -c "from pycat_napari import __version__; print(__version__)" # Then launch the GUI: pycat-napari (or equivalent entry point) Requires Python 3.12.x exactly; Python 3.13 and newer are not supported. Earlier versions (3.9, 3.11) are no longer supported as of v1.5.39. Verify before relying: - Whether the entry point command 'pycat-napari' is automatically created on install or requires manual setup. - Whether GPU acceleration via CuPy is automatically detected and enabled, or requires explicit configuration. - Whether the optional TrackMate integration (headless Fiji, ~500MB–1GB) is downloaded on first use or requires manual installation. - Performance and memory requirements for typical time-series or Z-stack workflows beyond the stated 8GB minimum. ## Package facts - License: License ------- BSD 3-Clause License Copyright (c) 2024, Christian Neureuter, Banerjee Lab, State University of New York at Buffalo All rights reserved. Redistribution and use in source and binary… (full text in the JSON record) (permissive) - Python support: capped_below_current - Install friction: low - Maintenance: active - Downloads: 297.0K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags condensate image analysis, biomolecular condensate detection, napari microscopy plugin, fluorescence image segmentation, biological image analysis tool, condensate quantification, microscopy data processing, microscopy, image-analysis, gui-application [View on SkillFed](https://skillfed.io/packages/pycat-napari) · [View on PyPI](https://pypi.org/project/pycat-napari/)