Multiplex image processing for challenging datasets with a focus on user integration rather than automation. This pipeline includes 2D/3D GPU/CPU illumination correction, stitching, deconvolution, extended depth of focus, registration, autofluorescence removal, segmentation, clustering, and spatial analysis.
To view notebooks in browser see: https://smith6jt-cop.github.io/KINTSUGI-docs/Intro.html
Download and install environment management software.
Download miniforge: https://github.com/conda-forge/miniforge.
Follow installation instructions for your OS.
Launch miniforge as administrator (if possible). You will be in the default “base” environment.
Change directory to your user folder:
cd C:\Users\[your user name]
cd /home/[your user name]
For Linux OS, you may need to enter:
source "${HOME}/miniforge3/etc/profile.d/mamba.sh"
source "${HOME}/miniforge3/etc/profile.d/conda.sh"
mamba activate
To download the code and associated files enter:
git clone https://github.com/smith6jt-cop/KINTSUGI.git
Change directory to enter the folder just downloaded
cd KINTSUGI
For Windows OS, create the environment by entering:
mamba env create -f environment.yml
For Linux OS, create the environment by entering:
mamba env create -f environment_linux.yml
The downloading and installation of the packages will take several minutes depending on available computing resources and network speed.
Activate the environment by entering:
mamba activate KINTSUGI
It is recommended to use VS Code to run the notebooks. Download and install VS Code https://code.visualstudio.com/.
Download zip files and extract them to KINTSUGI folder.
Java - Information at: https://www.oracle.com/java/technologies/downloads/#java21.
Download links:
https://download.oracle.com/java/21/latest/jdk-21_windows-x64_bin.zip (sha256)
https://download.oracle.com/java/21/latest/jdk-21_macos-aarch64_bin.tar.gz (sha256)
https://download.oracle.com/java/21/latest/jdk-21_linux-aarch64_bin.tar.gz (sha256)
Maven - Information at: https://maven.apache.org/download.cgi.
Download links:
apache-maven-3.9.9-bin.zip
apache-maven-3.9.9-bin.tar.gz
PyVips (LibVips) (for VALIS Registration only).
Windows download link: vips-dev-w64-all-8.16.0.zip
Additional install instructions for Linux: https://github.com/libvips/pyvips
FIJI/ImageJ: https://imagej.net/software/fiji/downloads
Install the "Fiji.app" folder to your user folder.
Follow clij2 installation: https://clij.github.io/clij2-docs/installationInFiji
Create a folder in the KINTSUGI folder called “data”.
If downloading test data use this link: https://uflorida-my.sharepoint.com/:f:/g/personal/smith6jt_ufl_edu1/Er5ui-wFA6BNnmgj9N1hPAsBYQaiKfSQa2do_lUMhQdaGg?e=5Uny95
Move all image data to [your user folder]\KINTSUGI\data.
1. Parameter tuning/testing For testing illumination correction, stitching, deconvolution, and EDoF.
2. Batch processing For batch processing illumination correction, stitching, deconvolution, EDoF, and registration.
3. Signal Isolation For autofluorescence subtraction, filtering, and final processing to isolate signal.
4. Segmentation For Mesmer segmentation and feature extraction.
5. Pixel Clustering For self-organizing map application to pixels.
6. Cell Clustering For self-organizing map application to pixel clusters and segmetation features.
Shoulders of giants we stand on:
For multiplex histology/imaging: Nolan lab
For illumination correction: Peng lab
For stitching: MIST, Fukai's m2stitch
For deconvolution: Becker's LsDeconv
For EDoF: Forster et al., Clij2
For registration: Gatenbee's VALIS
For segmentation: VanValen lab
For clustering: Angelo lab
For general processing: ImageJ/FIJI, pyImageJ, Haase's stackview
Python, Jupyter, conda/mamba, Java, Maven, Linux, Windows, UF, UFDI, Maigan Brusko Lab, NIH, HubMap, the power grid, the internet, the earth, gravity, the sun, oxygen, caffeine, love, neurons, neurotransmitters, water, the truth and the unkown.