Depictio goes live !¶

Depictio is now live with a public demo!

A longer demo is also available in Dashboard Creation Guide.

🎯 What is Depictio?¶

Depictio is an open-source, modern, web-based platform that aims to help life-science researchers and bioinformaticians to analyse complex data generated out of high-throughput experiments into interactive, shareable dashboards without requiring programming skills.

❓ Why Depictio and how does it differ from other tools (e.g., Shiny, Dash, Streamlit, Gradio, etc.)?¶

In bioinformatics, core facilities and research groups generating large datasets are relying on highly standardised workflows (e.g., nf-core pipelines) that produce structured outputs. These datasets require interactive exploration and visualization tools, helpful for quality control issues identification, as well as deriving actionable insights.

While there are multiple popular dashboarding solutions amongts bioinformaticians like Shiny, Dash, Streamlit, Gradio, they require programming skills and time to design tailored systems. This includes multiple steps, from the data ingestion to the data visualisation, as well as hosting and maintaining platforms in a production environment.

Depictio aims to fill this gap by providing a comprehensive platform composed of a cloud-compatible microservices architecture and a companion CLI tool (depictio-cli) living close to the data. The system provides a no-code dashboard creation experience that allows researchers to focus on data analysis.

🤨 Wait, but where is the life science focus in this ?¶

While the current version of Depictio is a general-purpose dashboarding tool (open-source alternative to Plotly Studio), the next phase (Q3-Q4 2025) is to have a strong focus towards life sciences domain-specific features.

On the frontend, this means bringing in specialized components (like JBrowse2 for genome visualization) and bioinformatics heavily used visualizations (like volcano plots, heatmaps, etc.) that are tailored for life science data.

On the backend and data ingestion side, our plan is to focus on developing seamless integration of MultiQC reports (gold standard in bioinformatics QC reporting) and to develop workflows templates for popular bioinformatics pipelines (like nf-core) to make it easy to aggregate, visualize and analyze aggregated results.

In the end, the idea would be to provide a comprehensive platform that allows life science researchers to easily create interactive dashboards using community-driven templates for established workflows.

In the spirit of MultiQC's automated data discovery for gold-standard bioinformatics QC tools (cutadapt, fastqc, ...) using multiqc . in a terminal, you would be able to run depictio --template nf-core/rnaseq . to automatically ingest workflow relevant data and fill a dashboard with pre-configured components for visualizing the results of a RNA-seq analysis conducted with nf-core/rnaseq pipeline.

👥 Who is it for?¶

Current users:

Researchers and data scientists seeking code-free dashboard creation
Anyone working with datasets who wants interactive exploration tools

Future target audience:

Life science researchers analyzing high-throughput experimental data
Bioinformaticians working with standardised pipeline outputs and multi-omics datasets

🎨 Main current features¶

No-code dashboard creation: Build interactive dashboards without writing code
Real-time interactivity: Play with your data using sliders, dropdowns, as well as box selection on scatter plots
Multi-data sources support: Combine multiple data sources (so-called Data Collections in Depictio) in a single dashboard using SQL-like joining system
Authenticated or Unauthenticated Access: Use the system with JWT-based authentication and Google Oauth or in unauthenticated mode (like the demo)
Docker-compose & Kubernetes ready: Easy deployment options for production use
Companion CLI (depictio-cli): Command-line interface for managing projects, scan data, and upload datasets

🛠️ Modern Architecture¶

Depictio is built on a state-of-the-art microservices architecture combining modern technologies for optimal performance, scalability, and developer experience. The system provides a comprehensive platform for interactive data visualization and analysis.

Frontend Technologies

Plotly Dash (React-based) interactive interface with Mantine UI components
Asynchronous Backend

High-performance async FastAPI backend with Python for real-time updates
Metadata Storage

MongoDB for project metadata, configurations, and user management
Data Storage

Delta Lake for optimized data storage and time-travel capabilities
Object Storage

MinIO S3-compatible storage for scalable file management
Data Processing

Polars engine for high-performance data manipulation and Delta Lake storage
Authentication

JWT-based authentication with Google OAuth integration
DevOps & Deployment

Docker and Kubernetes support for cloud-native infrastructure

Architecture Overview¶

The system is designed with a clear separation of concerns:

🎨 Frontend Layer: React-based dashboard interface with Plotly visualizations and Mantine UI components
⚙️ API Layer: FastAPI backend handling authentication, data operations, and real-time updates
💾 Data Layer: MongoDB for metadata, Delta Lake for analytics data, MinIO for object storage
🚀 Processing Engine: Polars for high-performance data manipulation and analysis
🔧 CLI Tool: depictio-cli for project management, data scanning, and automated workflows

👥 Who is behind Depictio?¶

Depictio is an open-source and academic project initiated by Thomas Weber, Research Fellow at the European Molecular Biology Laboratory (EMBL) during his ARISE fellowship (Marie Skłodowska-Curie Actions ; grant agreement No 945405). The project is primarily supported by the EMBL Data Science Centre with additional contributions from the SciLifeLab Data Centre.

🔬 Who is currently using Depictio?¶

Depictio is currently being used by EMBL researchers and data scientists across different life science fields. Some specific use cases include:

Strand-seq biobank (Korbel group, EMBL Heidelberg): Single-cell DNA sequencing to study Structural Variants (SVs) in human genomes. Pipeline used: mosaicatcher-pipeline
Marine microbiome interactome study (Vincent group, TREC, EMBL Heidelberg): Marine microbiome analysis using single-cell amplicon sequencing. Pipeline used: nf-core/ampliseq

🚀 How to Try It Out¶

Access the live demo at demo.depictio.embl.org or start using it below directly and explore the features. You can also create your own project and upload datasets to start dashboarding. Don't forget to check out the guides for step-by-step instructions on how to use the system.

Note

The demo is running a "unauthenticated mode" to allow anyone to try it out without needing an account. However, you can create a temporary account to create your own projects and upload datasets. Accounts and related data will be reset after 1 hour to keep the demo environment clean.

Live interactive demo - Try it!

🎮 What You Can Do in the Demo¶

1. Explore Pre-loaded Demo Datasets ..¶

Iris and Palmer Penguins datasets for quick visualization (Palmer penguins was turned into a sequencing runs-like dataset to showcase the system)

2. .. or Upload Your Own Data¶

Create your own project and upload datasets in your favorite tabular format (CSV, Parquet, etc.)

3. Create Interactive Dashboards¶

Figures: Scatter plots, bar charts, histograms, ...
Tables: Sortable, filterable data tables
Metrics Cards: Key performance indicators
Interactive Components: Sliders, dropdowns, segmented controls, and more

4. Experience Real-time Interactivity¶

Use box selection on scatter plots
Apply multiple filters simultaneously
Reset filters with a single click

🗺️ What's Next?¶

Get a look at our roadmap to see what we're working on next:

Support MultiQC Integration - Seamless quality control workflows
JBrowse2 Integration - Interactive genome browser for genomic data
TUI (Terminal User Interface) for project creation - Create project configuration using UI on the terminal
Workflow Templates - Pre-configured dashboards for popular pipelines like nf-core

🤝 Join Our Community and Contribute¶

Depictio is open-source and community-driven. We welcome contributions, feedback, and ideas to make it better!

🐙 GitHub: github.com/depictio/depictio
💬 Discussions: Share feedback and ask questions
🐛 Issues: Report bugs or request features
⭐ Star us: Help spread the word!

Questions? Feedback? We'd love to hear from you! Open an issue on GitHub or reach out directly.

Thomas Weber
August 2025