The evidence matters.
So do its limits.
A genomic finding becomes useful through careful interpretation. Our approach begins with what was measured, asks what the evidence supports, and keeps uncertainty visible.
Four questions behind
a responsible interpretation.
What was measured?
An interpretation begins with the assay and the observed data. Missing information needs to remain missing; it cannot become a reassuring result simply because a file contains no entry.
What supports the claim?
Evidence should match the specific variant and the meaning attributed to it. A database association is a starting point for review, not a substitute for evaluating its relevance.
Where does it apply?
An assay, a reference population and a clinical question each define scope. A result established in one setting cannot automatically support the same conclusion in another.
Who reviews the conclusion?
Technical checks and professional judgment have different roles. Clinical use needs an appropriate validation and review process, including the patient’s broader context.
“Not assessed”
is useful information.
A limited test may miss a relevant genetic change. An inconclusive result cannot establish or exclude a diagnosis. Clear reporting needs to explain that uncertainty.
Read the National Library of Medicine’s explanation of genetic test results.
Learn how to read result languageDifferent questions need different evidence.
Medication response
Explore where genetic information fits in prescribing, and which questions belong in a conversation with a healthcare professional.
Read the PGx field noteInherited conditions
Understanding carrier screening means understanding what a test checks and what remains outside its reach.
Read the carrier field noteYour DNA data
A raw file, a laboratory result and an interpretation have different roles. Understanding their relationship helps set useful expectations.
Read the data field noteOutside this laboratory pilot.
We do not currently report polygenic risk scores as part of the laboratory pilot offering described here. Offering a score requires validation of the model, relevant population, assay coverage and missing-data approach. That work cannot be replaced by a larger list of variants.
Atlagene is discussing laboratory evaluations. This page describes our approach; it does not certify an assay, a clinical service or a specific result.
Your next chapter
in genomics starts here.
Bring your questions, your workflow,
and your ambition. We’ll start there.