Project Vision: Automated Genomics Analysis Platform
From raw data to interactive exploration in minutes, not weeks
❌ The Current State of Genomics Analysis
Researchers spend weeks running standard analyses (DESeq2, GSEA) that only confirm known biology
Unknown genes get ignored because there's no literature to reference
Results come as static PDFs with tables that can't be explored interactively
Each new dataset requires writing custom analysis code from scratch
No easy way to navigate gene relationships or discover novel patterns
✅ Our Vision: End-to-End Analysis Platform
Upload your genomic data → Get an interactive web report with AI-powered exploration tools
Upload Data
RNA-seq counts, sample metadata, experimental design..
Configure Analysis
Choose analyses: clustering, networks, ML classification, dose-response. ML suggests optimal parameters.
Automated Processing
Backend runs full statistical pipeline: normalization, clustering, network analysis, enrichment..
Interactive Report
Deployed web app with force graphs, UMAP visualization, AI chatbots, gene prioritization..
🎯 Proof of Concept: Senescence Reversal Analysis
This site demonstrates the platform analyzing NANOG-mediated reversal of cellular aging in human muscle cells.
Dataset
Shahini et al. (2021) Science Advances
Platform Features
Scientific Insights
🔧 Reusable Components
Backend (Python)
- ✓ Modular Python pipeline: clustering, network analysis, ML, enrichment
- ✓ Works across mouse/human, aging/reprogramming contexts
- ✓ Produces structured JSON outputs for frontend
Frontend (SvelteKit)
- ✓ Force-directed network graphs (D3.js)
- ✓ UMAP cluster visualization
- ✓ Dose-response trajectory charts
- ✓ Gene prioritization tables with sorting/filtering
- ✓ Context-aware AI chatbots
- ✓ External data integrations (MyGene, UniProt, STRING, PubMed)
🚧 Path to Full Automation
Backend Automation
- ○ ML-assisted parameter selection (cluster count, thresholds)
- ○ Automated analysis selection based on data type
- ○ Smart preprocessing for different sequencing platforms
- ○ Advanced network construction methods
- ○ Batch processing for multiple datasets
Generic Frontend
- ○ Configuration-driven UI (zero hardcoding per dataset)
- ○ Dynamic component loading based on available analyses
- ○ User-customizable dashboards
- ○ Export reports (PDF, interactive HTML)
Platform Launch
- ○ Upload interface for raw data
- ○ Analysis wizard with ML suggestions
- ○ Cloud processing backend
- ○ Hosted reports with shareable links
- ○ Collaboration features
👥 Who Benefits
Academic Researchers
Skip weeks of coding, get interactive results immediately, share live reports with collaborators
Biotech Companies
Rapid target discovery from internal datasets, standardized analysis pipelines, publication-ready figures
Core Facilities
Offer value-added services beyond raw data delivery, differentiate from competitors
Funding Agencies
Interactive reports make grant applications more compelling, demonstrate data-driven decision making
⭐ The Impact
Democratizes genomics: No coding required to explore complex datasets
Accelerates discovery: Find patterns in hours that would take weeks manually
Reveals unknowns: Force graphs help researchers see relationships with uncharacterized genes
Reproducible science: Every analysis documented with parameters, thresholds, software versions
Share insights: Live web reports are more impactful than static PDFs
🚀 Try It Yourself
Explore this proof-of-concept analyzing 6,613 genes across young, senescent, and NANOG-treated myoblasts. Click through clusters, genes, and force graphs. Chat with AI assistants on every page. See what automated genomics analysis could look like.
Try these features:
- → Navigate via force graphs - click any gene to explore its network
- → Ask AI chatbots about mechanisms, pathways, or specific genes
- → View dose-response trajectories with individual sample data