A simple toolbox of two ImageJ plugins for quantifying adipocyte morphology and function in tissues and in vitro.
Note: If you are not seeing this readme file at https://github.com/hansenjn/AdipoQ/ please visit this page to get the most recent version of and information about AdipoQ.
- AdipoQ_Preparator_-…-SNAPSHOT.jar (Download latest release here): An ImageJ plugin to segment objects (i.e., adipocytes, lipid droplets, nuclei) from background.
- AdipoQ_Analyzer_-…-SNAPSHOT.jar (Download latest release here): An ImageJ plugin to quantify objects (i.e., adipocytes, lipid droplets, nuclei) from a segmented image or a multi-channel image featuring at least one segmented chanenl.
- R markdown templates for post-hoc analysis are available here.
All the tools are optimized for studying adipocytes in stained tissue or in vitro after immunofluorescent labeling.
A comprehensive User Guide is available here.
In addition, we provide a quick-start and an example guide for analyzing cells and histological samples.
Recently, StarDist fails to run unless also "Tensorflow" is installed in FIJI through FIJI's update manager. If you want to use the StarDist method, make sure to install "Tensorflow".
- Quick-start guide that teaches you the most important information for a first try of AdipoQ on an image of cultured cells.
- Example guide that walks you through the analysis of an example fluorescence microscopy image of cultured adipocytes using AdipoQ. The images used in the guide can be downloaded here:
- Soon we will provide here also a quick-start guide for using machine-learning (StarDist)-based predictions to detect nuclei in AdipoQ. Meanwhile, please read the notes on StarDist in the main user guide.
- Quick-start guide that teaches you the most important information for a first try of AdipoQ on an image of HE-labeled adipose tissue.
- Example guide that walks you through the analysis of an example image of HE-labeled adipose tissue with AdipoQ. The image used in the guide can be downloaded here:
When using any of the AdipoQ plugins or R scripts, please cite the following preprint:
Katharina Sieckmann, Nora Winnerling, Mylene Huebecker, Philipp Leyendecker, Dalila Juliana Silva Ribeiro, Thorsten Gnad, Alexander Pfeifer, Dagmar Wachten, Jan N. Hansen. AdipoQ—a simple, open-source software to quantify adipocyte morphology and function in tissues and in vitro. Molecular Biology of the Cell 2022, 33:12. doi: https://doi.org/10.1091/mbc.E21-11-0592
The source code for the plugins is available in the repositories for the individual plugins:
If you encounter problems, error messages, or would like to suggest / contribute new functions please use the issue systems on the respective repositories or send an email to jan.hansen (at) uni-bonn.de.
Copyright (C) 2019-2023: Jan N. Hansen.
AdipoQ has been developed in the research group Biophysical Imaging, Institute of Innate Immunity, Bonn, Germany (Lab Webpage).
Contacts:
- jan.hansen (at) uni-bonn.de
- dwachten (at) uni-bonn.de
The plugins are published under the GNU General Public License v3.0. A copy of the license is contained in this repository.