MISA++: A modular and high-performance framework for image analysis

Ruman Gerst (1,2), Anna Medyukhina (1), Marc Thilo Figge(1,2,*)

(1) Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute, Jena, Germany

(2) Faculty of Biological Sciences, Friedrich-Schiller-University Jena, Germany

* To whom correspondence should be addressed.

https://applied-systems-biology.github.io/misa-framework/

About

Segments cells with a distance transform watershed method.

Copyright

Copyright by Ruman Gerst

Research Group Applied Systems Biology - Head: Prof. Dr. Marc Thilo Figge

https://www.leibniz-hki.de/en/applied-systems-biology.html

HKI-Center for Systems Biology of Infection

Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Insitute (HKI)

Adolf-Reichwein-Straße 23, 07745 Jena, Germany

The project code is licensed under BSD 2-Clause. See the LICENSE file provided with the code for the full license.

Requirements

This project requires Python 3 and various dependency libraries. You can use pip to install the required libraries:

pip install -r requirements.txt

Usage

The program can be run with following command:

snakemake -j <num-threads> --config input=<input-directory> output=<output-directory>

The input directory must have following structure:

<input-directory>/<sample>/in/data.tif

There can be as many samples as required.