Ingest any format
WGS VCF, variant lists, credible sets, TSV, CSV, Parquet. Normalize once, get a clean variant table.
Annotate locally
Up to 54 functional annotation columns across all 24 chromosomes. Pathogenicity, frequency, conservation, regulatory scores. Runs on your hardware.
Add tissue context
eQTL, sQTL, apaQTL across 50 tissues, ChromBPNet predictions, enhancer-gene links. See where your variants act.
Rare-variant association testing
STAAR single-study analysis: Burden, SKAT, ACAT-V, STAAR-O. Bring your genotypes, phenotypes, and covariates.
Cross-biobank meta-analysis
MetaSTAAR for combining rare-variant results across multiple biobanks using summary statistics. No individual-level data sharing needed.
From tissue-specific regulatory data to the full 508 GB annotation database.
| Pack | Size | Contents |
|---|---|---|
| FAVOR Base | 200 GB | 40 curated columns: pathogenicity, frequency, clinical, conservation, regulatory, aPC STAAR channels |
| FAVOR Full | 508 GB | All 54 annotation columns including dbNSFP, ENCODE, MaveDB, COSMIC |
| eQTL | 3 GB | GTEx v10 eQTL/sQTL/apaQTL, 50 tissues, SuSiE fine-mapped |
| Single-cell eQTL | 48 GB | OneK1K, DICE, PsychENCODE |
| Regulatory | 18 GB | cCRE tissue signals, chromatin states, accessibility |
| Enhancer-Gene | 12 GB | ABC, EPIraction, rE2G, EpiMap, CRISPRi |
| Tissue Scores | 5 GB | ChromBPNet, allelic imbalance |
Every command outputs structured JSON. Point an AI agent like Claude at your genome data and let it run the entire analysis, interpret the results, and surface what matters.
Automated functional genomics
An AI agent can take a VCF, annotate it, enrich with tissue data, run association tests, and write up which variants are likely causal, which genes they affect, and in which tissues. What takes a bioinformatician days becomes a single conversation.
Works with Claude Code, Cursor, or any coding agent
The CLI ships with an agent reference that describes every command, its inputs and outputs, so agents know exactly what to call and how to read the results.
The goal is to replace entire bioinformatics workflows with single commands.
Interpretation
Score each variant for pathogenicity, map it to a target gene and tissue through enhancer-gene links and eQTL colocalization, layer in functional validation from CRISPRi and MPRA screens, and assign a confidence tier
Quality Control
Flag problematic samples and variants before analysis
Reporting
Generate publication-ready plots: Manhattan, QQ, locus zoom, tissue heatmaps
Walkthrough coming soon
One command to install. Open source. Free.