NucDetect 0.13.36

Module to identify intranuclear proteins on basis of fluorescence images.

NucDetect - A python package for Detection and Quantification of DNA Doublestrand Breaks

NucDetect is a Python package for the detection and quantification of γH2AX and 53BP1 foci inside nuclei. Its written in pure Python 3.7, obeys the PEP 8 style guidelines and includes PEP 484 type hints as well as Epytext docstrings.

Note

The current release is a very early alpha version. Please report report any detected bugs and/or improvement suggestions.

Requirements

NucDetect is compatible with Windows, Mac OS X and Linux operating systems. It requires the following packages:

• tensorflow>=2.1.0
• numpy>=1.18.1
• scikit-image>=0.16.2
• matplotlib>=3.1.3
• pyqt5>=5.14.1
• numba>=0.48.0
• pillow>=7.0.0
• qtawesome>=0.6.1
• piexif>=1.1.3

Installation

Run the following commands to clone and install from GitHub

$ git clone https://github.com/SilMon/NucDetect.git

or pypi

python3 -m pip install NucDetect

Start

The program can be started by running the NucDetectAppQT.py:

cd %UserProfile%/AppData/local/Programs/Python/python37/Lib/site-packages/gui
python -m NucDetectAppQT

First start: Switch to the created NucDetect Folder, which will be created in User directory. Then place images you want to analyse into the images folder and click the reload button. This will load all images and create a thumbnail for each (needed to decrease the memory footprint of QT). This can take several minutes, depending on the number of images and used hardware (e.g. around 5 min for 2200 images on a Ryzen 3700X processor). Progress will be displayed in the command prompt.

Supported Image Formats

Following image formats are supported by NucDetect:

• TIFF
• PNG
• JPG
• BMP

Not supported

• Grayscale images
• Binary images

Wiki

Detailed information about the program can be found on the

Supplementary Data

https://github.com/SilMon/NucDetect_Additional_Data

---

Author: Romano Weiss

Co-Author: Stefan Rödiger