Kana

Abstract

1. Introduction

These can be especially hairy when your backend server lies in a different jurisdiction from your data source. By performing the analysis on the client, we avoid all of these issues.

There's no need to maintain a server or cloud compute instance - let the user's machine take care of it. It also naturally scales to any number of users as they're automatically providing the compute.

This ranges from steps such as animated dimensionality reductions to user-driven marker detection and celltype annotation.

2. Objective

Single cell analysis in the browser

This project demonstrates how JavaScript can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/kanaverse/kana.git
cd kana

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by kanaverse and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.