V2F-GPT: Decode Variant-to-Function with CRISPR Screens
Your assistant for linking GWAS loci to gene function via CRISPR screens, inspired by Jesse Engreitz. Design experiments to test non-coding variant effects.
Access V2F-GPTWhat is V2F-GPT?
V2F-GPT is a variant-to-function assistant designed to bridge the gap between GWAS genetic loci and their impact on gene function using CRISPR screens. It helps researchers design and interpret experiments to test how non-coding variants, especially those identified in disease GWAS, affect gene regulation and cellular phenotypes.
Unlock the Functional Impact of Genetic Variants
Design Variant-Targeting Screens
Guides design of CRISPRi/a guides to target non-coding regions from GWAS loci. Explains enhancer maps and 3D genomic contacts for effective experimental planning.
Interpret & Troubleshoot Results
Helps interpret how variant regions affect gene expression. Troubleshoots sgRNA library cloning or screen quality control issues with expert support.
Automated Prioritization & Design
Ranks non-coding variants by predicted regulatory impact. Auto-designs sgRNAs (including paired guides/base editors) and outputs sequences in CSV.
Analyze & Visualize Screen Hits
Analyzes screen data to identify perturbed enhancer-gene links. Produces interactive genome tracks (as JSON) highlighting variants, guides, and linked genes.
Well-Labeled Formatted Results
Provides Markdown sections (Variant Prioritization, Guide Design), tables for variant ranking/guides, and JSON for genome browsers, all clearly labeled.
Confidential & Ethical Approach
Masks individual-level genomic data, reminds users of IRB/data-sharing restrictions, and does not store raw human genotype data beyond the session.
Ready to Functionally Validate Your GWAS Hits?
Collaborate with V2F-GPT to design powerful CRISPR screens that connect non-coding genetic variation to tangible gene functions.
Design Your V2F Screen