HiVis is associated with the following manuscript: Subcellular mRNA localization patterns across tissues resolved with spatial transcriptomics
HD Integrated Visium Interactive Suite (HiVis)
- HiVis is a user-friendly Python tool for analyzing
10X VisiumHD data,
supporting both H&E and immunofluorescence experiments. - HiVis is built on top of AnnData, integrating seamlessly with other spatial transcriptomics tools such as Scanpy and Squidpy.
- HiVis provides extensive data visualization with fully customizable plots. Plots are created using matplotlib, allowing stacking and further customization.
- HiVis works with
QuPath
to enable easy manual annotation, pixel classification, and single-cell segmentation using
Stardist,
Cellpose and Instaseg. It links bins and single-cell objects, facilitating seamless information exchange across levels.
Getting started
Installation
To avoid dependency conflicts, we recommend the use of a dedicated conda environment. In a terminal run the command:
conda create -n HiVis python=3.12
conda activate HiVis
We recommend two options to then install HiVis in your virtual environment.
Use the package manager pip to install HiVis. Takes up to few minutes. In a terminal run the command:
pip install HiVis
Or clone the project's Github repository and install it manually with the following commands:
git clone git@github.com:roynov01/HiVis.git
cd HiVis
pip install .
To use Qupath features, such as manual annotations and pixel classifiers, download and install QuPath (>= 0.5.1).
To perform cell segmentation in QuPath, download and install Stardist and/or Cellpose extensions for QuPath.
Usage and Documentation
For video tutorial - please refer to the tutorial playlist.
Please refer to the demo notebooks.
For QuPath, please refer to the tutorial.
Function docstrings are available on ReadTheDocs.
Code used for data analysis in the paper is available at the repo.
Contact
Bug report/feature request via the GitHub issue tracker.
Citation
Novoselsky R*, Golani O*, Barkai T, Kedmi M, Goliand I, Fine M, Kent I, Nachmany I, Itzkovitz S. Subcellular mRNA localization patterns across tissues resolved with spatial transcriptomics. Nature Communications, 2026.
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