GenomeNarrator: A Continuous, Auditable Personal Biology Engine
GenomeNarrator is not a one-time DNA report. Upload your 23andMe, AncestryDNA, MyHeritage, FTDNA, or VCF genome file once — including whole-genome and whole-exome sequencing (WGS/WES) VCFs up to 2 GB — entirely in your browser. GenomeNarrator does not run the sequencing itself; it analyzes the VCF file you already have from any WGS/WES source (a clinical lab, Nebula Genomics, Sequencing.com, etc.), in addition to SNP-array exports from 23andMe and AncestryDNA. Your raw genome file never leaves your device. No third-party access. Every report combines two risk models — monogenic (ACMG/ClinVar single-gene findings like BRCA1/2) and polygenic risk scores (PRS) from GWAS + PGS Catalog for complex conditions like cardiovascular disease and type 2 diabetes — plus pharmacogenomics, ancestry, and a diet/exercise/sleep Lifestyle Blueprint. Then layer recurring bloodwork on top of that genome, any time — from a PDF, a FHIR R4 JSON export, or a scanned report read via on-device OCR — reconciled against your own genetic findings so an out-of-range marker comes with a gene-level reason, tracked on a chronological Phenotype Timeline alongside a Model Resolution Score that quantifies how much of your biology is actually resolved. Preview your results for free, or unlock a full report starting at $12.99 one-time or $9.99/month. No biology or genetics background is required — every finding is explained in plain English first, with the clinical detail available for anyone who wants to dig deeper.
How Genomic Analysis Works
Upload your genome file (the file never leaves your device) and the analysis cross-references over 100,000 genetic variants against peer-reviewed databases including ClinVar, SNPedia, and the GWAS Catalog. No AI or large language model generates your results. Every finding is a deterministic match against published clinical data. Results include polygenic risk scores (PRS), pharmacogenomic drug interactions, ACMG v3.3 secondary findings across 84 genes, and ancestry breakdown. Learn more about our science and methodology.
Clinical Databases Behind Every Finding
Every variant in your report links to a peer-reviewed source:
- ClinVar: NIH's archive of clinical variant classifications from accredited labs worldwide. We require a 2-star minimum review status. Visit ClinVar at NCBI.
- SNPedia: Community-curated database of 60,000+ SNP entries with clinical significance and direct PubMed references. Visit SNPedia.
- GWAS Catalog: NHGRI-EBI catalog of published genome-wide association studies linking variants to traits and diseases. Visit the GWAS Catalog.
- CPIC: Clinical Pharmacogenomics Implementation Consortium guidelines for drug-gene interactions. Level A and B coverage for 40 genes. Visit CPIC.
- gnomAD v4.1: Population allele frequencies from the Genome Aggregation Database, used to contextualise variant rarity. Visit gnomAD.
- PGS Catalog: EBI's catalog of validated polygenic score models, used to build ancestry-adjusted risk scores for complex conditions. Visit the PGS Catalog.
Every finding is cross-referenced against these independent sources rather than a single lookup — the citation is shown per-finding in your report so you can verify it yourself.
An Interactive Dashboard, Not Just a PDF
Your results don't just land as a static PDF — they open in a full interactive web dashboard. This is the primary way you use GenomeNarrator; the Compass PDF builder and Doctor/Clinical Summary PDF are optional exports generated from that same dashboard, not the primary experience.
- Hero stat bar — an at-a-glance summary of your variant count, condition count, high-risk findings, and hereditary (ACMG) findings the moment your report loads.
- Priority Insights — every finding is auto-ranked by urgency and evidence tier, so the most actionable results (medication safety alerts, ACMG secondary findings, high-risk conditions) surface first instead of being buried in a linear document.
- Drill-down report sections — Overview, Ancestry, Hereditary (ACMG SF findings), Conditions (chronic disease risk and PRS), Medications (pharmacogenomics), and Molecular Detail (shared-pathway convergence, GTEx tissue expression, gnomAD gene constraint, and eQTL data per gene), each its own tabbed view rather than one long scroll.
- Interactive PGx Medication Checker — enter your own current medication list and cross-reference it live against every gene flagged in your pharmacogenomics results.
- Ancestry visualization — an ancestry composition breakdown across 8 gnomAD super-populations plus per-chromosome local-ancestry "chromosome painting," rendered as interactive charts, not static numbers.
- Data-freshness tracker — a live banner that quantifies exactly what's changed in ClinVar, the GWAS Catalog, and the PGS Catalog since your last analysis, with one-click re-analysis.
- Lifestyle tab — Diet & Nutrition, Exercise & Fitness, Sleep, Neurobehavioral, and Supplements chapters, browsable independently of any PDF export.
- Compass tab — build and customize your PDF report from inside the dashboard itself.
- 4 selectable visual themes (Native, Light, Dark, Forest) with live preview, so the dashboard matches how you like to read.
- Account panel — manage your subscription, security, and analysis history in the same interface.
What's In Your Report — Every Claim, Sourced
These are GenomeNarrator's own specifications — not a comparison against other tools. Each row below cites the primary source used to verify it.
| Capability |
What GenomeNarrator does |
Verify it |
| Plain-English Translation | Every finding is explained in everyday language first — what it means and why it matters — with the underlying ClinVar/CPIC/ACMG clinical data shown underneath for anyone who wants to verify it, never required reading. Not a raw database lookup. | Shown per-finding in your report |
| Data Sources | Six independent databases cross-referenced per finding: ClinVar, SNPedia, GWAS Catalog, PGS Catalog, gnomAD v4.1, and CPIC — not a single-source lookup | Our methodology |
| Pharmacogenomics (PGx) | 40 genes · 110 CPIC Level A/B drug-gene pairs, plus an interactive Medication Checker that matches your own current drug list against every flagged gene | CPIC guidelines |
| Whole Genome / Exome Sequencing (WGS/WES) | VCF files up to 2 GB accepted and analyzed directly, in GRCh37 or GRCh38 — not limited to SNP-array data | Upload a WGS/WES VCF |
| ACMG Secondary Findings | All 84 genes on the official ACMG SF v3.3 panel, screened — actionable findings paired with ClinGen-sourced next steps (surveillance, preventive options, medication guidance), including a dedicated surgical-anesthesia alert for RYR1/CACNA1S malignant hyperthermia carriers | Lee et al. 2025, Genetics in Medicine |
| Polygenic Risk Scores (PRS) | 1,000+ disease models — cardiovascular, type 2 diabetes, and other complex/metabolic conditions — from published GWAS + PGS Catalog | PGS Catalog |
| Bayesian Absolute Risk | Ancestry-matched priors from gnomAD v4.1 (807,000+ individuals) | Our methodology |
| Ancestry Composition | Auto-inferred across 8 gnomAD super-populations from ancestry-informative markers, with a confidence score, 95% CI, and sub-population refinement | Our methodology |
| Local Ancestry (Chromosome Painting) | Per-chromosome ancestry-segment painting via HMM & Viterbi decoding — validated to 89–94% window accuracy for high-divergence population pairs, 70–84% for closely related ones | Our methodology |
| Maternal / Paternal Haplogroups | mtDNA (PhyloTree Build 17) and Y-DNA (32 curated ISOGG-defining SNPs) haplogroup calls with confidence scoring, ancestral lineage, and migration path | Our methodology |
| Carrier / Compound-Het | Zygosity-aware carrier flags + phase-checked compound-het calls | Our methodology |
| Population / Founder Carrier Panels | 8 ancestry-specific founder-mutation panels (Ashkenazi Jewish, Finnish, African, South Asian, Middle Eastern/North African, East/Southeast Asian, European, Americas/Latino) covering 56 curated founder variants, auto-screened once your inferred ancestry for that population reaches 5%+ | Our methodology |
| Traits & Lifestyle Blueprint | 119 curated traits; 56 wired into evidence-graded (A/B/C) diet, exercise, sleep, and stimulant-metabolism recommendations across 5 pillars | Trait catalog |
| Client-Side Processing | Your raw genome file never leaves your device | How this works |
| Evidence Audit Trail | Every finding cites its source record — ClinVar accession, GWAS study, PGS ID, or SNPedia entry | Shown per-finding in your report |
| Finding Confidence | Every finding carries an Evidence Grade (0–100) and a ClinVar review tier — Expert Panel, Multiple Submitters, or Single Submitter | How grading works |
| Database Currency | ClinVar + GWAS Catalog rebuilt monthly; gnomAD, PGS Catalog, and CPIC refreshed each major release — your dashboard quantifies exactly what's changed since your last analysis, not just a generic reanalyze prompt | Our data sources |
| Interactive Dashboard | Results open in a full interactive web dashboard, not just a static PDF: a hero stat bar (variant/condition/high-risk/hereditary counts), Priority Insights auto-ranked by urgency and evidence tier, drill-down Overview/Ancestry/Hereditary/Conditions/Medications/Molecular Detail sections, the interactive PGx Medication Checker, ancestry composition plus per-chromosome local-ancestry chromosome painting, a data-freshness tracker with one-click re-analysis, a Lifestyle tab, a built-in Compass PDF builder, and 4 selectable visual themes with live preview | See it live — free demo |
| Molecular Detail | Every gene behind a finding gets its own drill-down: shared-pathway convergence across genes, GTEx tissue-expression body map, gnomAD gene-constraint (pLI/LOEUF) scoring, and expression-QTL data — a sortable cross-gene summary table plus an expandable per-gene card grid | See it in the dashboard |
| Blood Lab Panels | Standard bloodwork PDFs parsed into 46+ biomarkers across 10 panels — CBC, Lipid, Glucose, Liver, Kidney, Thyroid, Iron, Vitamins, Inflammatory, Muscle Enzymes — with trend tracking and a Body Systems overview plotting every monitored panel on a body map, colored by worst flag | See it in the dashboard |
| Lab Ingestion Formats | Bloodwork parsed from a standard PDF, a FHIR R4 JSON export (Bundle/Observation resources), or a scanned/photographed report read via on-device OCR, all parsed client-side and never uploaded raw, or values typed in by hand with each one flagged against its reference range as it is entered | See it in the dashboard |
| Genetics x Labs Crossover | 38 genes linked to 41 of the 46 biomarkers, each link carrying its evidence grade, source and last review date. A result is read as matching the genetic prediction, opposite to it, or in range, and a gene that was checked and does not carry the relevant variant is reported as not the explanation, so a flagged value points elsewhere instead of being pinned on DNA | See it in the dashboard |
| Biological Map | For every gene-to-lab link: what the gene does and the organ it acts in, with its GTEx v10 expression there and its Reactome pathway where the reference data has them. The organ is chosen for the biology of that lab value, not the tissue where the gene happens to be most expressed, and every expression figure and pathway is checked against the reference data by automated tests | See it in the dashboard |
| Testing Plan | Which blood tests are worth considering next, ranked by what a result would actually change for the person rather than by how alarming a gene sounds. Tests that only matter if a specific medication is started are listed separately and never pushed as a reason to test now | See it in the dashboard |
| Unknowns Engine | A Model Resolution Score weighs every genetic finding, PGx phenotype, and lab biomarker by evidence strength to quantify how much of a person's biology is actually resolved, and ranks the specific next lab panel that would close the largest gap — not a generic reminder to get more labs done | See it in the dashboard |
| Phenotype Timeline | A chronological view merging dated lab results with a person's fixed genetic and lifestyle findings into one timeline, so trends and static context sit side by side instead of in separate tabs | See it in the dashboard |
| Population Reference Bands | NHANES 2017-2018 population reference-interval bands rendered behind a person's own lab trend line, so an individual result can be read against a real population distribution, not just a single lab's flag threshold | See it in the dashboard |
| Clinician Summary (Genetics × Labs) | A separate 1-page export distinct from the Doctor/Clinical Summary PDF, bucketing the genetics×labs cross-reference into Concordances, Discordances, and Actionable Unknowns for a physician visit | Full pricing |
| Compass Report Builder | Customizable PDF report engine, available from the Essentials tier, covering every body system and finding in your analysis, not a fixed static export | Full pricing |
| Doctor / Clinical Summary PDF | Separate multi-page physician summary covering ACMG SF findings, PGx phenotypes, and pathogenic variants — built for sharing with a doctor, not a raw data dump | Full pricing |
| Try Before You Buy | A bundled demo genome unlocks the full Complete-tier report instantly in your browser — no signup, no payment, no DNA file required | Try the demo |
| Raw Data Export (CSV) | Every condition and trait match exportable as spreadsheet rows — risk category, confidence, variant count, matched RSIDs | Full pricing |
| Price | $12.99 one-time (30-day access) or subscriptions from $9.99/mo with ongoing re-analysis | Full pricing |
Pharmacogenomics: How Your Genes Affect Medications
The pharmacogenomics section identifies how your CYP2C19, CYP2D6, VKORC1, DPYD, and SLCO1B1 variants affect your response to common medications including warfarin, clopidogrel, SSRIs, statins, and chemotherapy agents. All findings follow CPIC Level A and B guidelines. Read our pharmacogenomics guide to understand how star alleles and phenotype predictions work.
Disease Risk Across 1,000+ Conditions
Your report covers cardiovascular disease, cancer predisposition (including BRCA1/2 and Lynch syndrome via ACMG secondary findings), neurological conditions such as Alzheimer's disease (APOE), metabolic disorders such as type 2 diabetes, autoimmune conditions, and rare Mendelian diseases. Complex, multi-gene conditions are scored with polygenic risk scores (PRS) computed from validated GWAS associations, not just single-gene lookups. Learn how genome-wide association studies translate into risk estimates.
Privacy by Architecture
GenomeNarrator was built from day one so that your raw genome file itself never touches a server. It is parsed and read directly in your browser. There is no storage of your raw DNA, and no third-party analytics that touches your genetic data. See our privacy policy for the full details.
Pricing
GenomeNarrator offers a free preview (2 body systems, 3 trait insights, and an ancestry summary) so you can see the pipeline before purchasing. Full access to all 1,000+ conditions, pharmacogenomics, and ACMG secondary findings is available as a $12.99 one-time 30-Day Pass (no subscription), or as an ongoing Essentials subscription from $9.99/month ($79.99/year). Plus ($14.99/month) adds the full Traits tab and the combined Compass PDF with every chapter, and Complete ($24.99/month) adds the Lifestyle Blueprint and a Doctor/Clinical Summary PDF. See full pricing for all five tiers.
Frequently Asked Questions
What genome file formats does GenomeNarrator support?
We support raw data files from 23andMe (.txt), AncestryDNA (.txt), MyHeritage, FTDNA, and standard VCF files in GRCh37 or GRCh38 format — including whole-genome and whole-exome sequencing (WGS/WES) VCFs. Files up to 2 GB are supported, and large WGS VCFs are streamed and parsed client-side rather than loaded into memory all at once. You do not need a premium subscription with your provider — just download the raw data file.
Do I need a background in biology to understand my results?
No. GenomeNarrator is built for people without a genetics background. Every finding starts with a plain-English explanation of what it means and why it matters, before any clinical terminology. ClinVar accessions, CPIC guideline levels, and ACMG classifications are shown for anyone who wants to verify a finding independently, but they are never required reading to understand your own report.
Is my genetic data private and secure?
Yes. Your raw genome file is parsed in your browser and never leaves your device — it is never uploaded. No third-party access to your raw DNA. We never sell or share your genetic data.
How accurate is the genomic analysis?
Clinical variants are cross-referenced against ClinVar with a 2-star minimum review status and CPIC Level A pharmacogenomic guidelines. Polygenic risk scores use validated GWAS associations from the NHGRI-EBI Catalog. SNP arrays only detect common, pre-selected positions — rare pathogenic variants and structural changes need whole genome sequencing (WGS) coverage to be assessed at all. If you already have a WGS or WES VCF file, GenomeNarrator analyzes it directly and gets that deeper coverage; if you only have 23andMe/AncestryDNA data, a clinical WGS panel is the way to close that gap.
Do I need a 23andMe or AncestryDNA account to use GenomeNarrator?
No. You only need the raw data file, which you can download directly from your testing provider's website under account settings or data downloads. The analysis works with any raw genome file in the standard tab-separated SNP format.
Does GenomeNarrator calculate polygenic risk scores (PRS)?
Yes. Alongside monogenic ACMG/ClinVar findings for single-gene conditions like BRCA1/2, every complex condition in your report — cardiovascular disease, type 2 diabetes, and 1,000+ others — is scored with a multi-SNP polygenic risk model built from published GWAS and PGS Catalog data, then Bayesian-adjusted against gnomAD allele frequencies for your inferred ancestry.
Does GenomeNarrator give diet, exercise, or lifestyle recommendations?
Yes. The Lifestyle Blueprint (Complete plan) turns 56 curated genetic markers into evidence-graded (A/B/C) recommendations across five pillars: Nutrigenomics (diet & nutrition), Exercise Physiology, Sleep & Chronobiology, Stimulant Metabolism, and Taste & Temperament.
How much does a genomic analysis cost?
You can preview your results for free. Full reports start at $12.99 for one-time 30-day access, or from $9.99/month as a subscription — Plus adds the full Traits tab and one combined PDF of every chapter, and Complete adds the Lifestyle Blueprint and a doctor-ready summary PDF. Visit our pricing page for all five tiers.
Is GenomeNarrator just a PDF report, or is there an interactive dashboard?
Both, and the dashboard comes first. After you upload a genome file — or try the free demo — your results open in a full interactive web dashboard: a hero stat bar, Priority Insights ranked by urgency, drill-down Overview/Ancestry/Hereditary/Conditions/Medications sections, an interactive PGx Medication Checker, ancestry composition and per-chromosome local-ancestry chromosome painting, a data-freshness tracker, a Lifestyle tab for diet/exercise/sleep recommendations, and 4 selectable visual themes. The Compass PDF builder and a separate Doctor/Clinical Summary PDF are optional exports generated from that same dashboard, not the primary experience.
What is the difference between a SNP array and whole genome sequencing? Does GenomeNarrator support WGS?
SNP arrays (used by 23andMe and AncestryDNA) test around 600,000 to 700,000 pre-selected genetic positions. Whole genome sequencing (WGS) reads every base pair in your genome. Yes — GenomeNarrator directly supports WGS: if you already have a WGS or WES VCF file (from a clinical lab, Nebula Genomics, Sequencing.com, or any other sequencing provider), you can upload it to GenomeNarrator and it is analyzed the same way as a 23andMe or AncestryDNA file, entirely in your browser, files up to 2 GB. GenomeNarrator does not perform the sequencing itself — it is not a saliva-kit lab — it analyzes the VCF a WGS/WES provider gives you. For most common disease risk and pharmacogenomics, SNP array data is sufficient; for rare disease diagnosis, BRCA confirmation, or comprehensive structural variant analysis, a WGS VCF gives deeper coverage than an array file. Read our guide on how genomes work for more.
Does GenomeNarrator use artificial intelligence to generate results?
No. Every finding is a deterministic lookup against ClinVar, SNPedia, CPIC, and the GWAS Catalog. No large language model or AI generates text in your report. The pipeline is open to review on our science page.
Is GenomeNarrator a one-time DNA report or an ongoing service?
GenomeNarrator is a continuous, auditable personal biology engine, not a one-time report. You upload your genome once, but ClinVar and the GWAS Catalog are rebuilt monthly, gnomAD/PGS Catalog/CPIC are refreshed each major release, and subscription tiers include ongoing re-analysis as that research updates. You can also layer in new bloodwork at any time — each lab result is reconciled against your existing genetic findings rather than replacing the report.
What happens when I upload a new blood test?
The lab result — from a PDF, a FHIR R4 JSON export, or a scanned report read via on-device OCR — is parsed entirely client-side, cross-referenced against your own genetic findings for a gene-level explanation of any out-of-range value, added to your Phenotype Timeline, and folded into your Model Resolution Score.
What is the Model Resolution Score and Unknowns Engine?
The Model Resolution Score is a figure that weighs every genetic finding, PGx phenotype, and lab biomarker by evidence strength to quantify how much of a person's biology is actually resolved versus still an open gap. The Unknowns Engine ranks the specific next lab panel that would close the largest remaining gap, rather than giving a generic "get more labs done" prompt.
Ready to understand your genome? Start your analysis. Upload takes under a minute — preview for free, or unlock the full report for $12.99 one-time or from $9.99/month.