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VariantScope is an educational gene variant explorer designed to answer whether disease-causing changes cluster in specific protein regions, whether those regions are confidently structured by AlphaFold, and how rare those variants are in the general population (README.md:1-6, docs/ARCHITECTURE.md:1-3).
The codebase is structured to ship from a single source code repository across three distinct deployment targets using a unified codebase architecture (docs/ARCHITECTURE.md:7-16).
Sources: README.md:1-6, docs/ARCHITECTURE.md:1-16
VariantScope provides a single modular codebase that compiles and runs in three deployment environments: as a desktop application built with Electron, as a static web application hosted on GitHub Pages, and locally via a development server (docs/ARCHITECTURE.md:7-16). Regardless of the target, application logic is cleanly partitioned into domain-agnostic data processing (src/core), DOM-rendering components (src/ui), stylesheet design systems (src/styles), and desktop integration layers (electron/) (docs/ARCHITECTURE.md:19-42).
Diagram: Deployment Targets to Code Entities
---
title: "Deployment Targets and Core Architecture"
---
graph TD
Deployment["Deployment Targets"] --> Electron["Desktop App electron/main.js"]
Deployment --> Web["Web Version GitHub Pages"]
Deployment --> Dev["Local Dev npm run dev"]
Electron --> Bridge["src/core/http.js getJson()"]
Web --> Bridge
Dev --> Bridge
Bridge --> Core["src/core/ Data Pipeline"]
Core --> UI["src/ui/ Visualization Layer"]
Core --> ElectronFetch["electron/fetcher.js"]
Sources: docs/ARCHITECTURE.md:7-42
To initialize the project, run local development commands, execute unit and end-to-end test suites, and review configuration parameters (Vite, Vitest, ESLint, Prettier, and Node.js requirements), consult the dedicated child page.
For details, see Getting Started.
Sources: docs/ARCHITECTURE.md:33-39, README.md:22-27
VariantScope integrates public bioinformatics databases—specifically UniProt for canonical protein sequences and accessions, AlphaFold DB for pLDDT structural confidence metrics, ClinVar for disease variant classifications, and gnomAD for population allele frequencies and gene-level constraint metrics (README.md:32-35, docs/ARCHITECTURE.md:46-56).
For details, see Domain Background and Data Sources.
Sources: README.md:32-35, docs/ARCHITECTURE.md:43-56
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