Origins & History
SYNTHETIC EXAMPLEIllustrative ancient-DNA reference neighbourhoods and broad modern-reference affinity.
- Historical windows are interpreted independently.
- No ancestry percentages are implied.
Illustrative example of the DNA_CHECKS consumer genetics report
The report is organised around Origins & History, Genetic Curiosities, Important Clinical Findings and Medication & Pharmacogenomics, followed by supporting evidence, technical traceability and source records.
Illustrative ancient-DNA reference neighbourhoods and broad modern-reference affinity.
Illustrative non-clinical associations covering senses, everyday biology, food response and performance.
Synthetic cards demonstrate evidence quality, inheritance, confirmation requirements and safety boundaries.
Illustrative coverage-aware gene calls show evaluated, unavailable and specialist-calling states.
This preview samples the main report surfaces rather than reproducing every possible record. A finished report can contain many more curiosity associations, clinical evidence records, pharmacogenomic evidence items, research-context records and technical provenance entries. The exact number varies with the uploaded DNA file and the evidence that passes the pipeline's quality and safety gates.
Genome-wide modern reference affinity and dated ancient-DNA reference history, shown here with synthetic examples.
Ancient comparisons are shown as affinity to dated reference neighbourhoods within separate historical windows. They are not ancestry percentages and do not claim direct descent from a named archaeological culture.
In this example, the synthetic sample sits relatively near an Upper Palaeolithic European reference neighbourhood within this chronological window.
Distance is model-specific geometry in a fixed PCA space. It is an affinity signal, not a probability or percentage.
This example shows how a later Neolithic reference neighbourhood can appear as the closest stable comparison for its own historical window.
The report can provide short source-backed archaeological context while keeping raw dataset labels and technical provenance behind disclosure.
A third synthetic period demonstrates chronological progression without implying that the ancient groups are components that add to 100%.
Each historical window is evaluated independently. Results should be read within that window rather than combined as an ancestry mixture.
The synthetic sample is shown near a broad modern European reference neighbourhood. DNA_CHECKS stops at the level supported by the reference model rather than inventing fine-scale nationality or ethnicity.
Fine-scale labels are shown only when reference data, validation and model stability justify that level of specificity.
Published non-clinical genetic associations presented as illustrative synthetic trait examples.
A synthetic TAS2R38-style example showing how DNA_CHECKS explains a non-clinical sensory association, including direction, evidence strength and population limitations.
A synthetic ABCC11-style example showing how a simple, well-studied everyday trait can be presented without implying clinical importance.
A synthetic example of a common behavioural/physiological association. The report explains that environmental factors and other variants can matter substantially.
A synthetic ACTN3-style example demonstrating how performance associations are framed as small probabilistic tendencies rather than deterministic predictions.
A synthetic sensory-preference example showing how DNA_CHECKS separates a published association from a deterministic prediction about what somebody will actually taste or like.
A synthetic smell-perception example demonstrating how a small everyday genetic curiosity can be explained alongside study-population and effect-size caveats.
A synthetic sleep-timing association illustrating how polygenic, lifestyle-sensitive traits are presented as tendencies rather than fixed biological outcomes.
A synthetic performance-related association showing how DNA_CHECKS keeps small statistical effects in context and avoids turning them into training prescriptions.
How high-priority clinical screening evidence is presented, using synthetic examples only.
DNA_CHECKS would describe the observed genotype, the relevant inheritance model, the quality and agreement of supporting sources, and why independent clinical confirmation is required before medical use.
A consumer SNP-array result can be useful for screening, but it is not a diagnosis. Consequential findings require confirmation by an accredited clinical laboratory.
This example demonstrates a finding that is retained because it may matter, but is not promoted to the highest-priority interpretation when source agreement, penetrance or technical certainty remains incomplete.
DNA_CHECKS separates source evidence from genotype certainty and can keep uncertain or conflicting evidence in supporting context instead of overstating it.
This synthetic example demonstrates how a potentially important dominant-inheritance observation would be separated from lower-priority associations and accompanied by confirmation, penetrance and family-context cautions.
Consumer-array data and interpretation are screening tools. A consequential result should be confirmed independently in an accredited clinical setting before medical decisions are made.
This synthetic example shows how DNA_CHECKS can retain a clinically relevant association while making clear that carrying an associated allele does not mean the condition is present or inevitable.
Evidence that is scientifically relevant but less deterministic is presented with lower prominence and stronger context rather than being promoted as a diagnosis.
Coverage-aware pharmacogenomic presentation with synthetic example calls and explicit safety boundaries.
DNA_CHECKS compares observed DNA with pharmacogene definitions, preserves missing positions as unknown and accepts only calls that pass coverage and diplotype safety gates.
The report distinguishes evaluated personal calls from guideline evidence records. A source database containing many PGx records does not mean the person has that many medication findings.
Example presentation of an intermediate-metabolizer-style result when sufficient allele-definition coverage is available.
DNA_CHECKS does not instruct the user to start, stop or change a medicine. Genotype-specific guidance is shown only when the evidence gate is satisfied.
Example presentation of a decreased-function-style call with coverage and source provenance exposed for review.
CPIC, DPWG, ClinPGx and FDA evidence are kept source-specific rather than collapsed into one undifferentiated recommendation.
This example demonstrates a pharmacogene that may be withheld from consumer-array calling when copy-number or complex haplotype resolution is insufficient.
An unavailable result is not treated as normal function. Missing or unresolved data remains explicitly unknown.
A synthetic example showing how an accepted metabolizer-style call can be presented alongside coverage information and source-specific clinical guidance.
Guidance remains tied to the relevant clinical source and does not become a universal medication instruction.
A synthetic example showing how DNA_CHECKS can distinguish an evaluated pharmacogene result from loci where consumer-array coverage is insufficient for a safe call.
The report does not direct dose changes. Medication decisions remain with an appropriate clinician or pharmacist using confirmed clinical information.
Lower-priority clinical, risk, protective and uncertain evidence retained for context and transparency.
Illustrative association retained for context because the effect is small, population-dependent or not appropriate for a prominent clinical conclusion.
Illustrative protective-direction association shown with the same caveats about effect size, population transferability and non-diagnostic meaning.
An example of conflicting or incomplete evidence that DNA_CHECKS keeps visible for transparency rather than silently discarding or over-promoting.
Gene-disease or variant-condition evidence that may be scientifically relevant but does not currently meet the main-report promotion gate.
An illustrative evidence card showing how population frequency can contextualise a variant without being treated as proof for or against disease in one individual.
An illustrative record showing how gene-level validity evidence can be retained separately from the interpretation of a specific observed genotype.
Structured provenance and traceability examples illustrating the technical audit layer.
| Record | Example value | Purpose |
|---|---|---|
| Input source | SYNTHETIC_PREVIEW | Identifies the input class without exposing a personal file. |
| Genome build | GRCh37 → GRCh38 | Documents coordinate normalization. |
| Evidence state | PREVIEW_ONLY | Prevents illustrative records being confused with real findings. |
| Evidence fingerprint | example_sha256_not_a_real_run | Shows where deterministic provenance appears in a real report. |
| Clinical finality | SCREENING_ONLY | Demonstrates the report's explicit clinical boundary. |
Representative scientific resources and source roles used by the DNA_CHECKS evidence system.
A real DNA_CHECKS report is generated from deterministic evidence pipelines. The scientific states, rankings, evidence gates, provenance and safety boundaries are not decided by generative AI.
DNA_CHECKS · public synthetic preview