Which DNA Testing Company Is More Accurate AncestryDNA or 23andMe

Which DNA testing company is more accurate: AncestryDNA or 23andMe?

For the raw genotype letters AncestryDNA and 23andMe report, there is no consistent accuracy winner. Both use the same broad type of array technology, and raw call reliability is similar for common markers, but any single accuracy percentage should be treated as illustrative rather than a formal published rate. For ancestry percentages, accuracy is the wrong word because there is no single correct percentage to compare against.

Judge a DNA file by whether the markers you care about are present, called and correctly mapped, not by which company's ethnicity algorithm feels more convincing.

Stop comparing two different things

The phrase 'more accurate' hides two separate tests. One test is raw genotyping: did the array read the base correctly at a known position? The other test is ancestry estimation: did a model place a window of your genome into the right reference group?

A consumer DNA kit does not sequence your entire genome. It uses a genotyping chip that measures fluorescent signal at hundreds of thousands of preselected SNP positions. Two allele-specific probes carry different fluorophores, one for each allele. The scanner reads the signal at each marker, and internal quality scores throw out calls that are not clear enough. That is why your raw file contains missing calls. A no-call is not a wrong call. It is the machine refusing to guess.

For the raw SNP question, both companies run tight quality control on common, well-performing markers. In validation-style comparisons, a high-quality array call often matches a sequencing-based call at the same site, and an illustrative figure is above 99%. That is not a formal published rate, and remaining errors cluster in low-performing markers and rare probes, plus copy-number regions. This is a real limit, but it does not give one company a practical accuracy crown.

Why ethnicity percentages cannot settle this

An ethnicity report is not a measurement of a fixed fact. The same DNA can be read against different reference panels and come out with different percentages. That does not mean one lab was more accurate and the other made a mistake. It means the model moved.

The mechanism works like this. Your genome is cut into windows. Each window is compared with reference populations from people whose ancestry is known over several generations. The software assigns each window to the best-fitting group and sums those assignments. The result depends on which reference groups exist, how many people are in them, how the algorithm smooths neighbourhoods, and what labels the company uses. When a company updates its reference panel, your percentages can change even though your raw file did not.

A person might get 12% Italian on one service and 18% on another. Neither percentage is a raw error because there is no fixed 18% sitting inside the genome waiting to be read. Italian is a modern label over a historically mixed population. Accuracy would require a ground truth that does not exist.

The follow-up question: which file should I use for health?

If you have a raw DNA file and want to look up a specific gene, the company name matters less than whether the file contains the relevant rsID and has it called. Both AncestryDNA and 23andMe files are generally accepted by third-party tools, but there are practical differences.

What to check in your own file:

• The rsIDs you actually need. For example, APOE is not a single SNP. You need rs429358 and rs7412 to make the common Alzheimer's-associated genotype call. Some tools may report APOE from partial data, which is less reliable.
• The genome build. Many health tools expect GRCh37 coordinates. A file that lacks coordinates or uses GRCh38 can be converted, but it is one more step where errors creep in.
• Call status. If the file says a particular marker is missing, a good tool should say so rather than silently guessing.
• File format. 23andMe and AncestryDNA both export tab-delimited text, but the header lines differ. That is a parsing issue, not a biological accuracy issue.

The common mistake is treating a consumer chip as medical-grade sequencing. Neither company comprehensively covers rare disease variants, and neither should be used as a diagnosis. But for many pharmacogenomic and trait markers, the genotype call at a covered site is usually reproducible.

What 'more accurate' would actually require

A real answer to the question would require the same saliva sample run through both company chips, plus whole-genome sequencing as the truth set, then a per-marker comparison across clinically relevant sites. That kind of public, current, independent comparison is not what most people are choosing from. Check each company's support documents for validation details, and treat any single accuracy claim as illustrative.

For raw health use, the practical ranking is:

1. 1.Whole-genome sequencing with clinical confirmation if you need broad coverage and rare variant screening.
2. 2.Either 23andMe or AncestryDNA raw files for checking common SNPs that the chip includes.
3. 3.Anything that hides the raw data or only gives a percentage without markers.

The order changes if you are looking for a specific variant. Then the winner is whichever file has that rsID called with a clean genotype.

The ancestry report is a model choice, not an accuracy choice

When you compare ancestry results, you are comparing how two companies chose their reference panels and cut points. A more detailed panel can create regions that sound more accurate but are just more specific. For example, separate Levant, Arabia, Anatolia/Iran, Caucasus and North Africa regions are a panel design, not a proof of superior accuracy.

If you already have a raw file, you can stop asking which company was more accurate and start looking at the markers that actually matter. The free DNA tool at HealthOS DNA accepts a raw 23andMe, AncestryDNA, MyHeritage or whole-genome VCF file. The raw file is parsed in your browser for trait and health findings. Only the optional ancestry step sends selected genetic markers to the server with explicit consent, not the whole file. The full report, which includes traits, medication response and carrier-relevant findings plus an optional genetic ancestry breakdown, requires a one-time email code. That is the more useful test: not which company read a chip, but what your file says.