<h2>Overview:</h2>
<p>The Visual Integration Tool for Exploration of Spatial Single-Cell Experiments, or Vitessce, is a versatile tool designed to enable interactive visual analysis of multi-modal assay types that probe biological systems using WebGL technology. It allows visualization of large datasets stored in cloud object storage without the need for managing compute infrastructure. Vitessce can be integrated into React projects and offers a range of interactive views such as scatterplots, spatial+imaging plots, genome browser tracks, and statistical plots.</p>
<h2>Features:</h2>
<ul>
<li><strong>Reusable Interactive Views</strong>: Including scatterplot, spatial+imaging plot, genome browser tracks, and control views.</li>
<li><strong>Integrative Multi-Modal Assay Analysis</strong>: Supports various assay types such as microscopy, genomics, and transcriptomics.</li>
<li><strong>Serverless Visualization</strong>: Ability to visualize large datasets stored in cloud object stores like AWS S3.</li>
<li><strong>Easy Integration</strong>: Can be seamlessly integrated into React projects.</li>
<li><strong>Development Support</strong>: Offers detailed guidelines for installation and development processes.</li>
<li><strong>Version Control</strong>: Utilizes changesets for managing changelogs and follows specific branch naming conventions for consistency.</li>
<li><strong>Testing and Deployment</strong>: Provides tools for testing, linting, and troubleshooting, along with deployment scripts for staging and publishing sites.</li>
</ul>
<h2>Summary:</h2>


<h2>Overview</h2>
<p>Vitessce-python is a Python API and Jupyter widget designed for the dynamic visualization of spatial single-cell data. This powerful tool facilitates complex data analysis through interactive visualizations, making it an ideal solution for researchers and data scientists in the field of bioinformatics. The integration with Jupyter notebooks enhances user experience, allowing researchers to delve into their data intuitively and efficiently.</p>
<p>By leveraging Vitessce-python, users can navigate through their single-cell data effortlessly. The tool stands out not only due to its visualization capabilities but also because of its robust installation and deployment process, which is streamlined for ease of use. Whether you're a seasoned professional or a newcomer to single-cell analysis, Vitessce-python provides a user-friendly platform for your data exploration needs.</p>
<h2>Features</h2>
<ul>
<li>
<p><strong>Interactive Visualization</strong>: Enables users to interactively explore spatial single-cell data, allowing for rich, multidimensional insights.</p>
</li>
<li>
<p><strong>Easy Installation</strong>: Can be installed simply using pip, making the setup process straightforward for users at any skill level.</p>
</li>
<li>
<p><strong>Jupyter Widget Integration</strong>: Seamlessly integrates with Jupyter notebooks, allowing for intuitive usage and enhanced interactivity during data analysis.</p>
</li>
<li>
<p><strong>Example Notebooks</strong>: Comes with example notebooks that showcase various use cases, helping users to understand and apply the tool effectively.</p>
</li>
<li>
<p><strong>Development Support</strong>: Features a development installation guide for advanced users, requiring NodeJS and NPM to facilitate customization and contribution.</p>
</li>
<li>
<p><strong>Troubleshooting Guidance</strong>: Offers a comprehensive troubleshooting section, assisting users in diagnosing issues with JavaScript console checks and environment configurations.</p>
</li>
<li>
<p><strong>Version Control for Deployment</strong>: Simplifies the deployment process through a GitHub Action workflow that automatically handles version updates and package uploads to PyPI.</p>
</li>
</ul>


Vitessce

Vitessce

Vitessce Python