BigFISH smFISH Analysis

A napari-plugin providing an alternative GUI for Big-FISH. Big-FISH is a python package for the analysis of smFISH images.

  • Volker Baecker

napari-bigfish

License MIT PyPI Python Version tests codecov napari hub

A napari-plugin providing an alternative GUI for Big-FISH. Big-FISH is a python package for the analysis of smFISH images.

The plugin provides a graphical user interface for some of the functionality in Big-FISH. Currently implemented are:

  • Gaussian-background subtraction
  • FISH-spot detection with
    • Elimination of duplicates
    • Auto-detection of threshold
  • Dense-region decomposition

The plugin further implements by itself:

  • Counting of spots per cell, inside and outside of the nucleus
  • Batch processing on a list of images

You can find the user and the api-documentation of napari-bigfish here.


This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.

Installation

You can install napari-bigfish via pip:

pip install napari-bigfish

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

Distributed under the terms of the MIT license, "napari-bigfish" is free and open source software

Issues

If you encounter any problems, please [file an issue] along with a detailed description.

Version:

  • 0.8

Last updated:

  • 2025-07-23

First released:

  • 2023-04-07

License:

  • MIT

Supported data:

  • Information not submitted

Plugin type:

Open extension:

Save extension:

Python versions supported:

Operating system:

  • Information not submitted

Requirements:

  • numpy
  • magicgui
  • qtpy
  • pyperclip
  • big-fish
  • scikit-image
  • tox; extra == "testing"
  • pytest; extra == "testing"
  • pytest-cov; extra == "testing"
  • pytest-qt; extra == "testing"
  • napari; extra == "testing"
  • pyqt5; extra == "testing"
Website by the napari team, original design by CZI. Go to napari main website.