How We Build Your DNA Reports

Scientific Methodology & Evidence Standards

Last reviewed: July 20, 2026

How GenesUnveiled Builds and Reviews DNA Reports

GenesUnveiled turns supported raw DNA files into understandable reports covering health risks, gene activity, pharmacogenetics, nutrition, traits, and other genetic findings. GenesUnveiled is an educational raw DNA interpretation service. It is not a clinical laboratory, diagnostic test, or substitute for a doctor, genetic counselor, pharmacist, or accredited genetic test.

Why We Created GenesUnveiled

GenesUnveiled is a small independent company created in Norway by two brothers interested in genetics, privacy, and what consumer DNA files can reveal.

We found that raw DNA information was often either difficult to interpret, spread across technical databases, or processed through services requiring people to upload and permanently store sensitive genetic data.

Our goal is to make selected genetic research easier to explore while keeping the user’s raw DNA file on their own device.

This means focusing on three principles:

Clarity: Genetic findings should be explained in understandable language.
Scientific transparency: Users should be able to see the evidence and limitations behind a report.
Privacy by design: Raw DNA analysis should not require permanent storage of a genetic file.

GenesUnveiled does not attempt to recreate a clinical genome test. We organize selected variants from supported consumer DNA files into educational reports that are easier to understand and investigate further.

Our DNA Report Research and Review Process

1. Identifying a Potential Genetic Report

Each report begins with a traceable scientific source, such as a peer-reviewed study, curated database record, or established pharmacogenetic guideline.

2. Reviewing the Available Research

The review may include:

Peer-reviewed human studies
Genome-wide association studies
Systematic reviews or meta-analyses
Functional studies
Clinical variant classifications
Pharmacogenetic annotations
Later publications discussing or attempting to replicate the finding
Study limitations reported by the researchers

Review depth is proportionate to the report type and evidence level. Interpretations are limited to conclusions that can be supported by the accessible source material.

3. Verifying the Variant

Before publication, we manually check:

The rsID
The associated gene or genomic region
The reported effect allele
The forward-strand allele representation
The direction of the reported association
Whether the required variant is available in compatible raw DNA files

If the allele direction cannot be resolved confidently, the report is not published.

4. Building the Genotype Interpretation

The user’s genotype is mapped into the result format appropriate for that report.

Depending on the report, this may include:

Lower, Typical, or Higher
Lower Activity, Typical Activity, or Higher Activity
Typical Response or Altered Response
Variant Detected or Variant Not Detected
A selected pharmacogenetic function category

Single-SNP reports normally compare zero, one, or two copies of the relevant allele.

Multi-variant reports use report-specific scoring rules. All required SNPs must be present before a multi-variant result is calculated. If a required SNP is missing or recorded as a no-call, the affected report is not calculated or shown.

5. Creating the User-Facing Report

AI-assisted and automated tools may support research organization, drafting, consistency checks, statistical calculations, and model testing. AI output is not treated as scientific evidence, and critical variant logic is manually checked before publication.

The final report is written to be:

Understandable
Practical
Non-deterministic
Proportionate to the evidence
Clear about important limitations
Appropriate for educational rather than clinical use

6. Publishing and Reviewing the Report

Published reports include scientific references and an evidence label where applicable.

Reports are reviewed on a rolling basis as new research, database classifications, pharmacogenetic information, or possible corrections become available.

Scientific Sources Used by GenesUnveiled

GenesUnveiled primarily uses the following resources:

Source	What it provides	How GenesUnveiled uses it	Important limitation
PubMed & peer-reviewed research	Human genetic studies, genome-wide association studies, meta-analyses, reviews, and functional research.	We evaluate the study design, population, sample size, effect direction, replication, effect size, and proposed biological mechanism.	Publication in a scientific journal does not automatically mean that a finding is strong, replicated, or clinically relevant.
ClinVar	Submitted interpretations of genetic variants associated with health conditions, including review status and supporting evidence.	We use it primarily for high-impact, pathogenic, carrier, and selected pharmacogenetic variants. We check review status and conflicting interpretations.	ClinVar submissions can disagree or change over time. A ClinVar listing alone does not establish that a variant is pathogenic.
PharmGKB / ClinPGx	Curated gene–medication relationships, clinical annotations, drug labels, guidelines, and supporting publications.	We research selected variants that may affect medication metabolism, transport, response, or susceptibility to adverse effects.	GenesUnveiled reports do not replace comprehensive haplotype, star-allele, or clinical pharmacogenomic testing.
NHGRI-EBI GWAS Catalog	Curated genome-wide associations between genetic variants and human traits, measurements, or health outcomes.	We use it to identify and verify variants for health, nutrition, gene, and trait reports, including the reported effect allele and study population.	A statistical association does not necessarily establish causation. Effects may be small or apply differently across populations.
NCBI dbSNP	rsIDs, allele information, genomic positions, reference assemblies, and other variant-identification data.	We use it to verify variant identity, possible alleles, and forward-strand representation.	dbSNP identifies and describes variants but does not establish that a health or trait interpretation is scientifically valid.

How We Evaluate Genetic Evidence

GenesUnveiled uses evidence labels rather than presenting every report as equally established.

Evidence labels are editorial assessments. They are not formal clinical classifications, numerical probabilities, or guarantees that a result will apply to a particular person.

Early Evidence (1/5)

The finding is preliminary or exploratory.

It may be based on:

One relevant human study
A relatively small sample
Limited replication
An early functional result
A population-specific association that has not been widely tested

Early evidence may be used for non-clinical traits or exploratory findings, but it should not be used alone to make health decisions.

Limited Evidence (2/5)

There is some relevant human evidence, but meaningful uncertainty remains.

It may be based on:

Small or moderate sample size
Limited independent replication
Inconsistent findings
Narrow population coverage
A small effect
Uncertainty about the biological mechanism

Limited evidence may be used for appropriately labeled exploratory reports, but it should not be used alone to make health decisions.

Moderate Evidence (3/5)

The association has reasonable scientific support.

This may include:

A well-designed genome-wide association study
Multiple broadly consistent studies
Replication in an independent population
Supporting biological or functional evidence
A consistent effect direction with no major unresolved conflict

Important limitations may still remain, particularly regarding ancestry, effect size, or how much of the trait is explained.

Strong Evidence 4/5)

The finding is supported by multiple substantial and broadly consistent sources.

It may be based on:

Large replicated human studies
A strong meta-analysis
Consistent clinical and functional evidence
A well-supported pharmacogenetic association
A curated variant classification with meaningful supporting evidence

Strong evidence does not necessarily mean that the effect is large or medically important.

Robust Evidence (5/5)

The finding has extensive and unusually consistent support.

This label should be reserved for associations supported by combinations such as:

Multiple high-quality replications
Expert-curated consensus
Established clinical classifications
Well-supported functional evidence
Widely accepted gene–variant or gene–medication relationships

Evidence Strength Is Not Effect Size

Evidence strength answers:

"How confident are we that the reported association is real?"

It does not answer:

How large the effect is
Whether the result is favorable
Whether someone will experience the outcome
Whether the finding is medically important
Whether the report represents someone’s complete genetic risk

A small genetic effect can have robust evidence. A potentially important finding can still have limited evidence.

Different Standards for Different DNA Reports

Health Risk Reports
Health Risk Reports evaluate a defined panel of variants associated with a condition, susceptibility, or health-related outcome. The reported direction of each selected variant is established from published human genetic research and incorporated into a report-specific score. For these reports, GenesUnveiled estimates a reference score distribution using population allele-frequency data and Monte Carlo simulation of one million simulated genetic profiles. The user’s combined score is then compared with this modeled reference distribution.

Depending on the outcome being described, results may use labels such as:

Less Likely
Slightly Less Likely
Typical or Typical Likelihood
Slightly More Likely
More Likely
Lower, Typical, or Higher for descriptive health characteristics

Every SNP required by the model must be present and callable in the raw DNA file. If a required SNP is missing or reported as a no-call, the report is withheld rather than generating an incomplete score.

These categories describe a modeled genetic tendency relative to the reference distribution. They do not provide an absolute probability, predict whether a condition will occur, establish a diagnosis, or mean that someone is protected from a condition. Age, ancestry, environment, lifestyle, medical history, and many untested genetic factors may also influence the outcome.

High-Impact Variant Reports

High-Impact Reports evaluate selected variants associated with potentially important findings.

They may include:

Pathogenic or likely pathogenic variants
Carrier-status findings
Pharmacogenetic function variants
Rare risk variants
Variants with unusually large or well-established effects

Unlike Health Risk Reports, High-Impact results are generally based on whether a particular reportable genotype or combination of genotypes is detected. They are not interpreted by comparing a polygenic score with a simulated population distribution.

Result wording may include:

No pathogenic variant found
No mutation found
No relevant variant detected
One copy detected
Two copies detected
Typical function
Altered or reduced function
Report-specific risk or protective wording

A result such as “No pathogenic variant found” means that none of the selected reportable variants were detected in the available raw DNA data. It does not rule out the condition, rule out carrier status, or confirm that the entire gene is unaffected. Likewise, detecting a selected variant does not by itself establish a diagnosis. Consumer DNA files may contain incorrect calls and do not cover all clinically relevant variation. Potentially important findings should be confirmed through an accredited clinical laboratory before they are used for medical decisions or family testing.

Gene Activity Reports

Gene activity reports use a principal SNP with an interpretable functional direction.

The selected variant may influence:

Enzyme activity
Gene expression
Receptor signaling
Protein function
Transporter efficiency
Promoter activity

Results may be presented as Lower Activity, Typical Activity, or Higher Activity.

A gene activity result reflects the selected variant. It does not measure the actual activity of the gene in the user’s tissues and does not account for every variant, regulatory influence, medication, or environmental factor affecting that gene.

Trait Reports

Trait reports generally use one or two selected SNPs and are presented as Lower, Typical, or Higher.

These reports describe genetic tendencies related to areas such as:

Physical traits
Food and taste preferences
Exercise response
Sleep tendencies
Behavioral tendencies
Sensory responses
Everyday biological differences

Traits are often influenced by many genetic and non-genetic factors. Early or limited evidence may be included when it is clearly labeled and the result is presented as an exploratory tendency rather than a prediction.

Pharmacogenetic Cards

The Pharmacogenetics section presents compact medication cards rather than complete clinical pharmacogenetic reports. Each card combines multiple selected SNPs associated with a specific medication outcome, such as metabolism, transport, biological response, or susceptibility to adverse effects.

Every card provides a short explanatory sentence together with a Low, Typical, or High category. The explanatory sentence is the primary interpretation because the meaning of the category depends on the outcome evaluated by that card.

In general:

Low indicates a lower modeled genetic signal for the specific outcome named on the card.
Typical indicates a result broadly similar to the card’s reference range.
High indicates a higher modeled genetic signal for the named outcome.

For example, Low may indicate no increased genetic tendency toward slow metabolism. It does not mean that the user has low metabolism, requires a low dose, or has a low overall medication risk. Similarly, High may refer to slower metabolism on one card and a higher likelihood of adverse effects on another.

Categories therefore cannot be compared directly between different medications. The explanation displayed on each card should always be read alongside its category.

Users should not start, stop, or change medication based only on these cards. Potentially important findings should be discussed with a qualified healthcare professional and confirmed through appropriate clinical testing when necessary.

Nutrition & Metabolism Cards

The Nutrition & Metabolism section presents compact genetic result cards rather than full reports. Each card is calculated from a defined panel of multiple SNPs associated with a nutrient-related trait, circulating level, utilization pattern, dietary response, or metabolic characteristic.

The selected alleles are combined according to the scoring rules created for that card. An “effect allele” is not automatically harmful or beneficial. It simply means an allele associated with the direction evaluated by that particular model.

Cards may display labels such as:

Lower Need
Slightly Lower Need
Typical Need
Slightly Increased Need
Increased Need
Lower, Typical, or Higher

The wording is adapted to the characteristic being evaluated. For example, a nutrient card may describe modeled “need,” while another card may describe a level, metabolic tendency, utilization pattern, or response.

The “Effect alleles found” count shows the genetic signal identified within that card’s multi-SNP panel. It is not an evidence rating, and counts should not be compared between cards because different panels contain different variants and use different scoring rules.

Terms such as “Increased Need” describe a modeled genetic tendency. They do not demonstrate a nutrient deficiency, measure current blood levels, or provide a supplement recommendation. Diet, laboratory results, medications, medical conditions, absorption, and other non-genetic factors may be more important than the genetic category.

Forward-Strand Alleles and DNA File Compatibility

GenesUnveiled stores report logic using the forward DNA strand.

Published studies and databases do not always present alleles in the same orientation. Before a variant is added, the effect allele is converted to and checked in forward-strand form.

Special caution is required for strand-ambiguous variants:

These allele pairs look the same after strand complementation. They are included only when the direction can be resolved using the rsID, original research, database records, provider format, or other reliable context. If orientation remains uncertain, the variant is excluded.

GenesUnveiled is designed for supported raw DNA files already using the expected forward-strand representation. It does not attempt to convert arbitrary reverse-strand files or every possible DNA format.

Variant coverage differs between providers and file versions. A report can only be generated when the required rsID and genotype are present in the selected file.

Missing Variants, No-Calls and Imputation

GenesUnveiled does not use imputation, proxy SNPs, or statistical guessing to replace a missing genotype.

If a required variant is:

Absent from the file
Recorded as a no-call
Unreadable
Presented in an unsupported format

the affected result is not calculated or shown.

This produces fewer results than estimating missing variants, but it avoids presenting an inferred genotype as though it were directly observed.

Who Curates GenesUnveiled Reports?

GenesUnveiled is a small independent Norwegian company built by two brothers with an interest in genetics, privacy, and making technical DNA information easier to understand.

Report research, curation, modeling, and final publication decisions are overseen by:

Sigve Klungsøyr
Co-founder and report curator

Our role is to organize published findings, create understandable selected-variant interpretations, explain uncertainty, and provide users with a private way to explore their existing raw DNA data.

Important Limitations of Raw DNA Analysis

Before interpreting any GenesUnveiled result, consider these limitations.

Consumer Raw DNA Files Can Contain Errors

GenesUnveiled does not collect a new biological sample or repeat the original genotyping. Results depend on the accuracy and coverage of the file produced by the original DNA provider.

Rare or medically significant findings are especially important to confirm independently.

Selected Variants Are Not a Complete Genetic Test

GenesUnveiled evaluates selected variants covered by the user’s file. It does not sequence the complete genome and does not examine every disease-causing or functional variant in a gene.

A typical result does not rule out other relevant variants.

Genetic Associations Are Probabilistic

Most common variants influence probability or tendency rather than determining an outcome.

Carrying an associated allele does not mean someone will develop a condition or display a trait. Not carrying it does not mean someone has no risk.

Ancestry Can Affect Relevance

Genetic research has historically overrepresented people of European ancestry.

Some findings and modeled reference distributions may therefore be less applicable to people from other ancestral backgrounds.

Environment and Personal History Matter

Genetic reports do not incorporate a user’s:

Symptoms
Medical history
Family history
Laboratory results
Diet
Exercise
Medication use
Environment
Age or life stage

These factors may be more important than the selected genetic variants.

Association Does Not Always Mean Causation

A SNP found through GWAS may be associated with an outcome without directly causing it. It may instead be linked to another nearby variant or reflect a more complex biological relationship.

Evidence Changes

Genetic research evolves. A finding may be replicated, weakened, contradicted, reclassified, or better explained as new evidence becomes available.

Report Updates and Review Dates

GenesUnveiled reviews and updates reports on a rolling, risk-prioritized basis. Priority is given to medically significant findings, pharmacogenetic interpretations, ClinVar classification changes, contradictory evidence, and credible correction requests.

Report a Scientific or Genotype Error

We welcome credible correction requests.

If you believe a report contains a scientific, citation, rsID, gene, allele-direction, genotype-mapping, or calculation error, please use the GenesUnveiled contact form.

You may also email support@genesunveiled.com

Please include, where possible:

The report title
The SNP or rsID
The suspected error
A relevant publication or database link
A screenshot without personally identifying information
Why you believe the direction or interpretation is incorrect

Potential errors affecting medically significant, pharmacogenetic, or variant-orientation results receive priority.

Please do not send your complete raw DNA file unless support specifically requests limited information needed to investigate a technical problem.

Privacy During DNA Analysis

GenesUnveiled is designed so that normal DNA analysis runs locally in the user’s browser.

During normal use:

The raw DNA file is selected from the user’s device.
Genotypes are read and matched locally.
Report calculations run in the browser.
The raw DNA file is not uploaded to GenesUnveiled.
The raw DNA file and per-variant results are not stored on GenesUnveiled servers.
The raw DNA file is not sent to an AI service.

Users must select and analyze their file again when beginning a new session.

Account, subscription, payment, website-security, and support information are handled separately from raw genetic analysis. More information is available in our Privacy and Security Policy.

How to Use Your GenesUnveiled Results

GenesUnveiled reports are best used as a starting point for learning and further investigation.

You can:

Read the cited research
Compare the evidence label with the size of the reported effect
Consider whether the research population is relevant to you
Explore how genes interact with environment and lifestyle
Discuss medically important findings with a qualified professional
Confirm serious or actionable variants through an accredited laboratory

Do not use a GenesUnveiled result by itself to diagnose a condition, rule out disease, change medication, determine treatment, or make major medical or reproductive decisions.

Explore your DNA privately, understand what the research suggests, and keep the limitations in view.

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