Coverage
Exactly what gets checked — and what your chip can’t see.
Indaga screens your data against industry-standard, graded, citable gene panels, then annotates findings from public, peer-reviewed databases. All of it runs locally, and all of it is honest about its limits.
~600–700k
positions directly genotyped
A consumer chip reads a fixed set of SNPs — a tiny, deliberately-chosen slice of the genome.
~70M
variants after imputation
Indaga imputes to a reference genome (Beagle + the 1000 Genomes 30× panel), reaching tens of millions of variants — with quality scores kept and surfaced.
callable / not
stated for every finding
Where a position can’t be trusted from your file, it’s reported as not callable — never as “you’re fine.”
Gene panels screened
The same panels clinicians and labs rely on.
- 84 genes
Actionable secondary findings
The medically-actionable, return-of-results genes recommended for reporting.
ACMG SF v3.3 (PMID 40568962)
- 113 genes
Carrier screening
The standard pan-ethnic carrier panel — 97 autosomal-recessive + 16 X-linked.
ACMG 2021 (PMID 34285390)
- 6,000+ relationships
Gene–disease validity
Every gene–disease link graded Definitive → Strong → Moderate → Limited → Disputed → Refuted.
GenCC + ClinGen
- PanelApp
Diagnostic panels
Curated green-gene diagnostic panels for focused questions.
Genomics England
- PGS Catalog
Polygenic scores
Published polygenic scores applied to your data, with overlap QC and percentiles.
PGS Catalog
- CPIC / DPWG
Pharmacogenomics
Drug-gene diplotypes and dosing guidance, gated on what was actually callable.
PharmCAT 3.2.0
Novel variants are classified with an automated ACMG/AMP engine across five tiers (pathogenic → benign), using protein-impact predictors and transcript-aware consequence calls — not a lookup table.
Explore it
549 genes, mapped — and every panel they connect.
One interactive map of everything Indaga screens: the panels as a radial ring, and the gene ↔ panel network where 158 genes bridge multiple panels. Hover the ring, drag the network, search a gene.
Every panel Indaga screens
Hover the ring to explore each panel.
- ACMG SF v3.384
- ACMG Carrier113
- PanelApp diagnostic281
- Wellness domains317
- Nutrigenetics13
How the panels overlap
The same gene often matters clinically and for wellness. Left/top: the tiers as flows into unique vs. shared genes. Then: which sub-panels share genes — the cardiac and hereditary-cancer clusters light up. Hover to explore.
Hover a cell — the diagonal is each panel's size, brightness is how many genes two panels share.
More ways to see your genome
Annotation sources
Public databases — downloaded, then queried on your machine.
Every interpretation is grounded in named, public, peer-reviewed sources. They’re downloaded once and queried locally, so your individual genes are never looked up in the cloud.
- ClinVar
- gnomAD (frequencies + constraint)
- PGS Catalog
- GWAS Catalog
- AlphaMissense
- REVEL
- MANE Select
- GenCC + ClinGen
- PanelApp
- Reactome
- Human Protein Atlas
- Gene Ontology
- 1000 Genomes
What the engine does
One engine, many lenses — all local.
Every capability below maps to the open-source engine. If it’s listed, it runs — on your machine.
- Clinical screen
- ClinVar P/LP, ACMG SF v3.3, carrier status
- Pharmacogenomics
- CPIC / DPWG dosing via PharmCAT
- Polygenic scores
- PGS Catalog, percentiles, overlap QC
- Variant classification
- automated ACMG/AMP, five tiers
- Diagnostic panels
- PanelApp + GenCC/ClinGen validity
- The Biological Clock
- circadian phase from your wearable
- Metabolic & glucose
- CGM time-in-range, dawn phenomenon
- Labs & biomarkers
- structured, callability-aware
- Multi-omic synthesis
- DNA × labs × wearable × glucose
Indaga provides wellness decision-support, not a medical diagnosis. Its insights are designed to be reviewed with a qualified clinician.
Indaga is in active development.
We’re building it in the open — privacy-first, cited, and honest about what it can and can’t see.