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Documentation Index

Fetch the complete documentation index at: https://docs.getbased.health/llms.txt

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getbased can overlay genetic context on your blood work. Drop a raw DNA file from AncestryDNA, 23andMe, or another major provider and getbased scans it for 47 health-relevant SNPs, then surfaces that context alongside the biomarkers you’re already tracking — so the AI can factor in your genetics when interpreting lab results. No account, no upload, no cloud processing.

Supported providers

You need a raw DNA data file from your testing service — not a PDF report or health summary, but the underlying data export.
ProviderFile formatHow to download
AncestryDNATab-separated textSettings → DNA → Download Raw DNA Data
23andMeTab-separated textSettings → 23andMe Data → Download Raw Data
MyHeritageCSVDNA → Manage DNA kits → Download Raw Data
FTDNA (Family Tree DNA)CSVmyFTDNA → Download Raw Data
Living DNATab-separated textDashboard → Download Raw DNA
Illumina GenomeStudioCSV with [Header]/[Data] blocksProvided by your clinical lab
getbased identifies files by their content headers, not the filename. If your file isn’t recognized, make sure you downloaded the raw data export and not a formatted health report.

How to import

Three entry points open the same file picker:
  • Dashboard card — when no DNA is loaded, the Genetics section shows an Add your DNA data card. Click it to open a file picker.
  • Drag and drop — drag your file anywhere onto the dashboard.
  • Chat onboarding — first-time users see a DNA prompt during the chat-driven setup wizard.
1

Open the file picker

Click Add your DNA data on the dashboard, or drag your raw DNA file onto the page.
2

Review the import preview

getbased groups your findings by impact level before saving anything. Significant results appear first.
3

Click Import

Confirm to save. The 47 matched SNP genotypes are stored in your browser. Everything else in the file is discarded.
No AI provider is needed for DNA import. The entire file is parsed locally using a Web Worker — your raw DNA data is never transmitted anywhere.

What gets extracted

getbased doesn’t store your genome. It scans your file for 47 curated SNPs across 13 categories and discards everything else. Each SNP was selected because it has a known biochemical mechanism, a large effect size, and directly helps interpret a biomarker you’re already tracking.
CategorySNPsExample genesRelated markers
Methylation6MTHFR, MTR, MTRR, CBSHomocysteine, folate, B12
Iron5HFE, TMPRSS6, TFFerritin, transferrin, iron
Lipids6APOE, PCSK9, CETP, LIPCLDL, HDL, cholesterol, Lp(a)
Vitamin D4VDR, GC, CYP2R1Vitamin D
Vitamin B124FUT2, TCN2, CUBNB12, homocysteine
Blood sugar5TCF7L2, PPARG, ADIPOQ, MTNR1BGlucose, HbA1c, insulin
Sex hormones5SHBG, CYP17A1, CYP19A1Testosterone, estradiol, SHBG
Thyroid3DIO1, DIO2, TSHRTSH, fT3, fT4
Bilirubin2UGT1A1Total bilirubin
Fatty acids4FADS1, FADS2, ELOVL2Omega-3, EPA, DHA
Alcohol1ALDH2GGT, AST, ALT
Caffeine1CYP1A2Cholesterol, hsCRP, glucose
Body composition1FTOBody fat %, BMI, HbA1c

APOE haplotype

The two APOE SNPs (rs429358 + rs7412) are automatically resolved into standard haplotype notation — ε2, ε3, or ε4 — rather than shown as raw genotypes. Your APOE status appears prominently at the top of the Genetics dashboard section.

Effect tiers

Each genotype gets a colored dot indicating how much weight to give the finding when interpreting your labs.
IndicatorMeaningExample
Red — significant riskMeaningful functional impact worth factoring into health decisionsMTHFR C677T AA (~30% enzyme activity)
Yellow — moderate riskMild effect, relevant when combined with other factorsHFE C282Y heterozygous
Orange — mild riskSmall effect on its own, mainly relevant in combinationMTHFR A1298C heterozygous
Green — beneficialA variant that’s actually good newsPCSK9 R46L (~15% lower lifetime LDL)
Gray — informationalA lab-interpretation flag, neither risky nor protectiveFUT2 W154X non-secretor (artificially high B12)
Wild-type genotypes with no meaningful effect get no dot. The import preview groups findings by severity so you see significant results first.

Where genetics appears

After import, your genetic context surfaces in four places across the app. Dashboard — a collapsible Genetics section shows your APOE haplotype and top findings grouped by category, sorted by severity. Initially shows up to 8 findings with a Show all button. Each finding links to its primary study on PubMed and a further-reading page on SNPedia. Biomarker detail modal — when you open any biomarker’s detail view, relevant SNPs appear inline with the gene, your genotype, and what it means for that specific marker. SNPs are sorted by severity. AI chat — the AI automatically receives your genetic context when interpreting lab results. Only SNPs relevant to the markers being discussed are included, unless you ask about genetics directly — then your full profile is sent. Context cards — SNPs route to the relevant context cards (diet, supplements, sleep, and so on) so the AI can factor them into lifestyle recommendations.

mtDNA haplogroup import

In addition to autosomal SNPs, getbased can determine your maternal haplogroup from a mitochondrial DNA mutation file.

Supported file format

Some labs (including Living DNA) export mtDNA results as a plain CSV with one mutation per line:
263G
462T
1438G
10398G
13708A
Drop this file onto the app and getbased will:
  1. Match your mutations against diagnostic markers from PhyloTree Build 17
  2. Resolve your maternal haplogroup (for example, J, H, U, or K)
  3. Classify your mitochondrial coupling status using Doug Wallace’s framework
  4. Compare your haplogroup against your profile’s latitude to detect environment-haplotype mismatch

Manual haplogroup entry

If you already know your maternal haplogroup from 23andMe, FTDNA, or another service but don’t have a mutation file, you can enter it directly without uploading anything:
  • Edit Client form — select your haplogroup from the dropdown under “mtDNA Haplogroup (maternal lineage)”
  • Chat onboarding — use the Enter haplogroup dropdown in the DNA step next to the upload button
Both paths auto-resolve the coupling classification and environment mismatch detection.

Coupling classification

Based on Wallace (2015, Cell), mtDNA haplogroups correlate with mitochondrial electron transport coupling efficiency:
  • Coupled (L lineages) — efficient ATP production, low heat generation. Evolved in equatorial climates.
  • Uncoupled (J, T) — more heat per calorie, less ATP. Evolved in cold northern climates.
  • Intermediate — most other haplogroups fall between these extremes.
The AI uses this to contextualize your lab results, cold tolerance, light exposure, and environmental data.
The coupling classification follows Wallace’s mitochondrial paradigm — supported by cybrid studies and population data, but not universally accepted as clinical standard. Individual variation within haplogroups is significant.

Privacy

Your raw DNA file never leaves your device.
  • The file is parsed entirely in your browser using a Web Worker — it is never uploaded or transmitted to any server
  • Only the 47 matched SNP genotypes are stored, not your full genome
  • Stored data includes the rsID, genotype, gene name, variant name, and effect classification
  • DNA data is included in your JSON exports and covered by encryption if you have it enabled
  • You can delete your genetic data at any time from the Genetics dashboard section

Re-importing

Importing a new file replaces all existing genetic data for the current profile. Use the Re-import link at the bottom of the Genetics dashboard section, or drop a new file onto the page. This is useful if you switch providers or download a newer export from your testing service.

FAQ

Quality over quantity. Each SNP was selected because it has a well-understood biochemical mechanism, a large effect size, and directly helps interpret a biomarker you’re already tracking. Adding hundreds of low-confidence GWAS associations would create noise rather than signal. Every SNP links to its primary research paper so you can verify the evidence yourself.
getbased identifies files by their content headers, not the filename. Make sure you downloaded the raw data export — a text or CSV file — and not a PDF report or formatted health summary. If you’re using Illumina GenomeStudio output from a clinical lab, confirm the file includes the [Header] and [Data] block structure.
Not directly through the app. The SNP list is curated and versioned — every entry must pass strict criteria: a known mechanism, large effect size, well-replicated findings, and clear actionability tied to a tracked biomarker. Community contributions are welcome via pull request on GitHub. Open an issue first with the rsID, which biomarker it maps to, the mechanism, effect size, replication evidence, and what concrete recommendation follows.
APOE status is determined by two SNPs — rs429358 and rs7412 — that must be read together. getbased combines them automatically into the standard notation (ε2/ε3/ε4) rather than showing raw genotypes. The most common result is ε3/ε3, which is considered the neutral baseline.
No. Genetic information provides context for interpreting your lab results — it does not diagnose conditions. Always discuss significant findings with your healthcare provider before making changes to supplements, medications, or treatment plans.
Only the 47 matched SNP genotypes: the rsID, genotype, gene name, variant name, and effect classification. Nothing else from your raw DNA file is retained. The full genome data is processed in memory and immediately discarded after the scan completes.