Welcome to SPARCStools documentation!

This python module contains wrapper functions to perform stitching with the Ashlar API. In addition it contains data parsing functions to make imaging data aquired with the Perkinelmer Opera Phenix Microscope accessible Ashlar or also to other downstream applications.

The generated stitched images can then be used for downstream applications, for example the SPARCSpy workflow or other analysis frameworks.

Installation

SPARCStools has been tested using python >= 3.8 on Linux and MacOS. Currently to run on Windows please utilize a Linux Virtual Machine.

Clone the github repository and navigate to the main directory:

git clone https://github.com/MannLabs/SPARCStools.git
cd SPARCStools

Create a conda environment and activate it

conda create -n stitching python=3.10
conda activate stitching

Install Java using conda

conda install -c conda-forge openjdk

Install package via pip. This should install all dependencies as well.

pip install .

Citing our Work

This code was developed by Sophia Maedler and Niklas Schmacke in the labs of Matthias Mann and Veit Hornung.

If you use our work please cite the following manuscript:

SPARCS, a platform for genome-scale CRISPR screening for spatial cellular phenotypes Niklas Arndt Schmacke, Sophia Clara Maedler, Georg Wallmann, Andreas Metousis, Marleen Berouti, Hartmann Harz, Heinrich Leonhardt, Matthias Mann, Veit Hornung bioRxiv 2023.06.01.542416; doi: https://doi.org/10.1101/2023.06.01.542416

Modules:

• Modules
  • parse
  • stitch
  • image processing

Tutorials:

• 1. Tutorials
  • 1.1. Parsing and Stitching Data from Opera Phenix
    • 1.1.1. Generated output
    • 1.1.2. Example Results

Example Notebooks:

• 1. Example Stitching Notebook
  • 1.1. Visualize Stitching Output