Get Health Insights From Your AncestryDNA Raw Data

AncestryDNA tests you on a DNA chip that reads roughly 650,000 to 700,000 positions, depending on when you tested. Ancestry chose the markers for genealogy, but most are the same kind of common variants found on other consumer chips, so the file supports the same health analyses.

The download is a single tab-separated text file, AncestryDNA.txt. Its layout differs from 23andMe's in a few ways that matter if you open it yourself:

#AncestryDNA raw data download
rsid	chromosome	position	allele1	allele2
rs4988235	2	136608646	A	G
rs12913832	15	28365618	G	G
rs1801133	1	11856378	0	0

• Two allele columnsEach copy has its own column (allele1, allele2) instead of a combined genotype like AG. They are unphased, so the order says nothing about which parent each came from.
• No-calls are 0A marker the chip couldn't read shows 0 in both allele columns.
• Sex chromosomes are numberedChromosome 23 is X, 24 is Y, 25 is the region X and Y share, and 26 is mitochondrial DNA.
• GRCh37 positionsPositions use the GRCh37 (hg19) reference genome, like other consumer files.

Ancestry has used more than one chip version, so two Ancestry files can overlap less than you might expect. Imputation (below) smooths this over for polygenic scores.

Ancestry launched a health product, AncestryHealth, in 2019 and later shut it down to focus on family history. Ancestry's site no longer gives health results, and it doesn't accept files from other companies, so the raw data download is the only way to get health information out of your test.

The file supports the same analyses as any consumer chip:

• Polygenic risk for common diseasesHeart disease, type 2 diabetes, breast and prostate cancer, and most other common conditions are shaped by thousands of common variants, each with a small effect. A polygenic risk score adds them up and compares your total with a reference population. The top of the distribution can matter: in one large study, about 8% of people had at least three times the average risk of coronary artery disease based on their score alone (Khera et al., Nature Genetics, 2018).
• APOE and other well-studied single variantsA handful of individual common variants matter on their own. Two markers, rs429358 and rs7412, together give your APOE type; carrying one or two ε4 copies substantially raises Alzheimer's risk. Others include HFE C282Y (rs1800562, hereditary hemochromatosis) and Factor V Leiden (rs6025, blood clots). Chips call these reliably because they are common, but anything with health consequences is worth confirming clinically. If you would rather not know your APOE type, avoid tools that report it.
• How you respond to medicationsCommon variants in genes like CYP2C19 and SLCO1B1 affect how your body processes many medications, including some antidepressants, clopidogrel, and statins. Genomisaur doesn't cover drug response, but our sister site Gene2Rx does: it reads the same raw data file and checks how your genes may affect 120 medications, with results based on clinical guidelines such as CPIC's. Get a pharmacogenetics report on Gene2Rx
• Physical and everyday traitsLactase persistence (rs4988235), blue versus brown eyes (rs12913832 in HERC2), wet or dry earwax (rs17822931 in ABCC11), and the alcohol flush reaction (rs671 in ALDH2) are each driven mostly by one well-mapped variant. Traits shaped by many genes, like height, are better estimated with polygenic scores.

Imputation stretches the file further. Because nearby variants tend to be inherited together, statistical imputation against a large reference panel can fill in millions of markers the chip never measured. Genomisaur imputes array files to about 30 million variants before scoring, so each score can use far more of its variants than the chip covers directly. Imputation is accurate for common variants and much less reliable for rare ones.

DNA chips are designed around common variation. They struggle with rare variants, and rare variants are where most high-impact disease mutations live.

• Rare variant calls are often wrongWhen a clinical lab re-tested variants that people had found in their consumer raw data, 40% turned out to be false positives (Tandy-Connor et al., Genetics in Medicine, 2018). In UK Biobank chip data, calls for the rarest variants were confirmed by sequencing only about 16% of the time (Weedon et al., BMJ, 2021). If any tool flags a rare disease-causing variant in your file, treat it as a reason to get a clinical test, not as a result.
• A clean result doesn't rule much outMore than a thousand disease-causing variants are known in BRCA1 and BRCA2. The best-known consumer BRCA report covers three of them, which are mainly found in people of Ashkenazi Jewish ancestry. Not seeing a variant in your raw data says little about whether you carry a different one.
• Some kinds of variation are invisibleChips cannot reliably detect deleted or duplicated genes (such as the SMN1 deletions behind spinal muscular atrophy carrier status), repeat expansions (Huntington's disease, fragile X syndrome), or most larger structural changes.
• Scores travel poorly across ancestriesMost genetic studies have been done in people of European ancestry, so polygenic scores predict less well in other groups. One widely cited analysis found accuracy 2 to 4.5 times lower in East Asian and African ancestry groups (Martin et al., Nature Genetics, 2019). Genomisaur's percentiles are calibrated against a European-ancestry reference, and its reports say so.

Ancestry's DNA matches only include people who tested with Ancestry. Uploading AncestryDNA.txt to GEDmatch, FamilyTreeDNA, or MyHeritage lets you find relatives who tested with other companies. Fees and features change, and some genealogy databases allow law-enforcement searches depending on your settings, so read each site's terms first.

The file opens in any text editor, and at a few hundred thousand rows it fits in a spreadsheet. Search for an rsID and you will find your genotype. A few things trip people up:

• StrandConsumer files report genotypes on the forward (plus) strand of the reference genome. Papers and SNPedia sometimes describe the same variant on the opposite strand, where A pairs with T and C pairs with G, so a "risk allele T" in a paper can appear as A in your file. Check the orientation before concluding anything.
• One SNP rarely means muchMost variants you will read about shift risk by a few percent. Without the thousands of other variants and a reference population to compare against, a single "risk" genotype is usually noise.
• Popular variants with weak evidenceMTHFR C677T (rs1801133) is the classic example. It is heavily marketed, but the American College of Medical Genetics and Genomics recommends against testing for it because it has little clinical value.
• Missing callsA marker the chip could not read means no data, not a normal result.

Services that accept raw data do quite different things. Choose by what you want to learn.

Before uploading anywhere, check three things: what method sits behind the health results (published polygenic scores, single-SNP lookups, or something proprietary), whether you can delete your data, and whether the company sells or shares it. Prices change often; confirm on each site.

Your raw data identifies you, and partly identifies your relatives. Once a copy sits on another company's server, you depend on that company's security and deletion policy.

In the US, the Genetic Information Nondiscrimination Act (GINA) bars health insurers and most employers from using your genetic information. It does not cover life, disability, or long-term care insurance.

Genealogy databases are a special case: some allow law-enforcement searches, usually depending on your settings. Check each site's options before you upload.