GeneGeniusRUO

Genetic data moves faster than interpretation.

Labs generate long lists of genetic variants, but interpreting what each one means takes time and specialized expertise. GeneGenius analyzes VCF files and provides ACMG/AMP classifications for evaluated variants, documenting the evidence criteria met and those that could not be evaluated.

NVIDIA Inception memberNVIDIA Inception Program

For research use only. Not for diagnosis, treatment, or clinical decision-making. A qualified person reviews the research result. GeneGenius does not make that decision.

The cost of the wait

Why this matters now

The meaning of a change is rarely in one place. Population data, published evidence, and a specialist's checklist have to be brought together by hand, after the sequence is already finished.

The cost of that wait is real. Rare disease diagnosis can take years, and the annual U.S. economic burden of rare disease is estimated to approach $1 trillion on 2019 data.

30M+
Americans living with a rare disease (roughly 1 in 10)
NORD Rare Disease Facts (2026)
5+ yrs
Typical time to diagnosis
NORD Rare Disease Facts (2026)
$517K
Upper bound of avoidable cost per patient from delayed diagnosis ($86K–$517K across seven rare diseases)
EveryLife Delayed Diagnosis Study (2023)
See the full picture: why this takes so long
The GeneGenius Workflow

From genomic data to research-ready evidence

GeneGenius helps research teams analyze genetic variants, connect findings to supporting evidence, and generate structured reports in one traceable workflow.

  1. 01VCF ingest
  2. 02Clinical parse
  3. 03Annotation
  4. 04ACMG/AMP interpretation
  5. 05Research report
Product Walkthrough

See GeneGenius in action

A walkthrough of the product, with the judgment calls left to an expert.

Analysis dimensions

What each result can include

Five parts of the analysis for each variant a run evaluates. Not every dimension is independently validated or live yet.

Classification

An ACMG/AMP classification for each variant the run evaluates, with the criteria that were met and the criteria that could not be evaluated. A criterion that could not be evaluated says why: not provided, turned off, not applicable, the source failed, or the model was unavailable.

Phenotype match

Can inform the phenotype criterion only when you supply real phenotype input (HPO terms, a short note or a text file) and turn Phenotype Match on in Settings. Validated on synthetic clinical notes; real-world EHR validation is in progress.

Splicing context

Available splice scores can inform the splicing criteria. A computational prediction, not an observation.

Structural context

A predicted effect on protein structure and stability, shown beside the call. It does not change the classification and is not a measured binding energy.

Other research context

Matched therapies from CPIC, PharmGKB, CIViC and JAX-CKB, not dosing guidance. A gene-level mechanism note that does not establish this variant's effect. A reanalysis flag that does not change the stored classification.

What we do

From a raw VCF to an interpretable, evidence-linked research report

We start where sequencing ends. Built for research teams, laboratory scientists, and clinicians working in a research setting.

See all services

Research Use Only · Not for diagnostic procedures

Organizational Value

Built for more genomic capacity with the teams you have.

GeneGenius is designed to help laboratories and research programs complete more genomic work with existing teams, keep more analysis in-house, and expand the services they can offer.

Capacity

Built for throughput

Designed to help teams complete more genomic analyses without increasing specialist headcount at the same rate.

Retention

Keep work in-house

Designed to reduce dependence on outsourced interpretation and keep more genomic work within the organization.

Services

Room to expand services

Built to support reanalysis, cohort research, evidence reporting, and new genomic research programs.

For hospitals and academic medical centers, this can also support larger research cohorts, biobank programs, sponsored studies, and pharmaceutical partnerships.