8cubeDB: Mouse Specificity Explorer 🐭

Exploring gene specificity in 8 tissues from 8 individuals for each of the 8 founder mouse strains

8cubeDB provides a unified platform to explore gene specificity, marker genes, and expression variability across founder mouse tissues from the Rebboah et al. (2025) dataset. It includes both a RESTful API (built with FastAPI) and an interactive dashboard (built with Streamlit).

---

🌐 Access the Platform

• Frontend Dashboard: https://mouseexplorer.onrender.com Explore genes, visualize Psi-blocks, and browse marker and housekeeping genes interactively.

• Backend API: https://eightcubedb.onrender.com/docs Programmatic access to the dataset via REST API. Refer to this colab notebook for a tutorial on how to query the database in python.

---

System Overview

FastAPI Backend

The backend serves data from two curated SQLite databases:

• 8cube.db — primary specificity and Psi-block data
• mean_var_DB.db — mean and variance of gene expression across conditions

All API routes stream data as CSV downloads for seamless integration with downstream tools.

Key Endpoints

Endpoint	Description
/	API root — overview of available endpoints
/config	Returns available analysis levels, types, and block labels
/specificity	Extract gene specificity data for given genes
/psi_block	Fetch Psi-block data by analysis level/type
/highly_specific	Retrieve genes highly specific to a given variable
/non_specific	Retrieve non-specific (housekeeping) genes
/marker	Identify marker genes by block label
/gene_expression	Get gene expression mean and variance values

---

Streamlit Frontend

The Mouse Specificity Explorer dashboard provides an interactive interface to visualize and query the API.

Main Features

Tab	Functionality
🔬 Gene Viewer	Visualize Psi-block and gene expression data for specific genes
🗺️ Specificity Explorer	Browse gene specificity across the dataset
⭐ Highly Specific Genes	Identify genes specific to a tissue or condition
🏠 Housekeeping Genes	Explore broadly expressed, non-specific genes
🎯 Marker Genes	Discover marker genes for selected blocks

Built with Streamlit, Plotly, and Pandas, the app offers clean visualizations and downloadable tables.

---

Data Summary

• Dataset: Rebboah et al. (2025) — 8cube founder mouse dataset
• Metrics: Ψ (Psi) specificity index and ζ (Zeta) selectivity metric
• Levels: Multi-scale analysis (cell type, tissue, organ, etc.)
• Sources: Derived from table_1 (global summary) and *_psi_block tables (block-level metrics)

---

⚙️ Architecture Overview

                ┌───────────────────────────────────────┐
                │      Streamlit Frontend               │
                │  (https://mouseexplorer.onrender.com) │
                └───────────────┬───────────────────────┘
                                │ REST API calls (CSV)
                                ▼
                 ┌──────────────────────────────────────┐
                 │        FastAPI Backend               │
                 │  (https://eightcubedb.onrender.com)  │
                 └───────────────┬──────────────────────┘
                                 │ SQLite Queries
                                 ▼
                    ┌──────────────────────────────┐
                    │        SQLite Databases      │
                    │   - 8cube.db                 │
                    │   - mean_var_DB.db           │
                    └──────────────────────────────┘

---

Project Attribution

Developed by Nikhila P. Swarna Pachter Lab, Caltech

Part of the IGVF Consortium Specificity analyses powered by ember.

---

License

Licensed under the BSD 2-Clause License. © 2025 Pachter Lab · All rights reserved.

---

Citation

If you use this website or the accompanying database, please cite the following papers:

• Rebboah E, et al. Systematic cell-type resolved transcriptomes of 8 tissues in 8 lab and wild-derived mouse strains captures global and local expression variation. (2025) DOI: https://doi.org/10.1101/2025.04.21.649844

• Swarna NP, et al. Determining gene specificity from multivariate single-cell RNA sequencing data. (2025) DOI: https://doi.org/10.1101/2025.11.21.689845