Welcome to SCOUT's documentation! ================================= .. image:: combined_render.jpg :width: 400px :align: center :alt: organoid_render SCOUT is an open-source Python package for performing volumetric image analysis of intact cerebral organoids. [1]_ The details behind the development of this package can be found in the following publication: .. [1] Alex Albanese*, Justin Swaney*, Dae Hee Yun, Nicholas Evans, Jenna Antonucci-Johnson, Vincent Pham, Chloe Delepine, Mriganka Sur, Lee Gehrke, Kwanghun Chung. 3D Imaging and High Content Morphological Analysis of Intact Human Cerebral Organoids. **Nature Methds (under revision)**, 2020. If you use SCOUT, please be sure to cite this publication in your work. The SCOUT package provides a command-line interface (CLI) for extracting multiscale features as well as a library of tools that can be mixed-and-matched to build custom single-cell organoid analyses pipelines. SCOUT also includes example Jupyter notebooks for users that prefer the more interactive, web-based development environment. .. toctree:: :maxdepth: 1 :caption: Tutorial installation test_data preprocessing single_cell proximity segmentation cytoarchitecture statistics .. toctree:: :maxdepth: 1 :caption: Main Modules preprocess nuclei niche segment cyto multiscale .. toctree:: :maxdepth: 1 :caption: Additional Modules io utils curvature detection score .. toctree:: :maxdepth: 1 :caption: Cheatsheet Modules analysis_cheatsheet Contributing ============= For those who want to add additional functionality to the existing SCOUT pipeline, a pull request can be submitted to the SCOUT repo. Feature requests can be submitted as issues on the SCOUT repo as well. Contact ======== If you have questions about SCOUT or how to use it, please submit an issue to the SCOUT Github repo. We welcome feedback from the organoid scientific community. Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` This site is maintained by members of the `Chung Lab`_ at MIT. .. _Chung Lab: http://www.chunglab.org/