Installation

Polarity-JaM - Feature Extraction Pipeline

The feature extraction pipeline is the process of extracting all relevant features from all input images. The result will always be a .csv file for each image containing its individual cells as rows and their corresponding feature values as columns. Additionally, plots will be created. These visualizations can be used for quality control but might also be suitable for a publication.

Manual installation with additional segmentation options

For additional support in segmentation, we suggest to install Polarity-JaM via micromamba and the conda-forge channel. For that, make sure you have micromamba installed. Manually install Polarity-JaM via:

micromamba create -y -n polarityjam python=3.8 pip -c conda-forge
micromamba activate polarityjam
pip install polarityjam

Manual installation without additional segmentation options

Make sure you have conda installed.

Execute the following steps to manually install Polarity-JaM with a working conda installation via:

conda create -y -n polarityjam python=3.8
conda activate polarityjam
pip install polarityjam

Automatic installation with album

Install album. This installation comes natively with micromamba. Then execute the following steps:

album add-catalog https://gitlab.com/album-app/catalogs/helmholtz-imaging
album install de.mdc-berlin:polarityjam:0.1.0

You can now run the pipeline with the following command:

album run de.mdc-berlin:polarityjam:0.1.0

Note

Please make sure you are using album version 0.10.4 (current version) for installation of the polarityjam solution.

Manual installation from GitHub

Make sure you have conda installed.

Execute the following steps on the commandline:

conda create -y -n polarityjam python=3.8
conda activate polarityjam
git clone https://github.com/polarityjam/polarityjam.git # via git or download via browser
cd polarityjam
pip install -e .

Polarity-JaM - Web App

The R-shiny Polarity-JaM web app further analyses the results of the feature extraction process in the browser. There are several statistics available which parameters can be adapted during runtime to immediately observe the change in the corresponding visualization. Thus, Exploring the data and relieving interesting patterns is heavily facilitated. To get to know more about the statics continue reading or visit the Methods section.

Note

You don’t need to install the web app to use the feature extraction pipeline. The web app is our visualization tool for the results of the feature extraction pipeline. You can simply use our online service here. Or visit software suite for more information.

Manual installation

Make sure you have conda installed. Alternatively, you can also use micromamba. If you do so, replace conda with micromamba in the following commands.

Execute the following steps on the commandline:

git clone https://github.com/polarityjam/polarityjam-app.git # via git or download via browser
cd polarityjam-app
conda env create -f polarityjam-app.yml
conda activate polarityjam-app
cd app
Rscript app.R

Open the browser in the URL given in the output of the R-shiny call (usually http://127.0.0.1:8888 ).

Automatic installation with album

Install album. This installation comes natively with micromamba. Then execute the following steps:

album add-catalog https://gitlab.com/album-app/catalogs/helmholtz-imaging
album install de.mdc-berlin:polarityjam-app:0.1.0

You can now run the pipeline with the following command:

album run de.mdc-berlin:polarityjam-app:0.1.0

A browser should automatically open. If not, open http://127.0.0.1:8888

Run with Rstudio

Alternatively, you can also open the app.R your local polarityjam-app/app folder with Rstudio and simply click on “Run App”.