--- title: "Upload a whole-genome VCF for ancient-DNA ancestry" description: "How to run an ancient-DNA ancestry analysis from a whole-genome sequencing VCF — tellmeGen, Dante Labs, Nebula and similar — what happens to the file at upload, why it is converted to the panel's markers, and what changes versus a chip export." canonical: https://www.ancestrify.io/blog/upload-whole-genome-vcf-ancestry date: 2026-08-28 updated: 2026-08-29 author: "Ancestrify" --- # Upload a whole-genome VCF for ancient-DNA ancestry If you had your whole genome sequenced — with tellmeGen, Dante Labs, Nebula Genomics or a similar provider — you were handed a very different file from the one a chip test gives you. It is enormous, it is in a format most consumer ancestry tools reject, and it holds far more information than any of them use. This guide explains how to run an ancient-DNA ancestry analysis on it, what happens to the file when you upload it, and what actually changes compared with a chip export. ## What a VCF is A VCF — Variant Call Format — lists the positions where your genome differs from a reference genome, with your genotype at each. Whole-genome sequencing produces millions of such positions, usually delivered as a compressed `.vcf.gz` file of several hundred megabytes; the specification was defined by Danecek and colleagues (2011). A chip export from 23andMe or AncestryDNA, by contrast, is a fixed list of roughly 600,000–700,000 positions the chip was designed to read, whether or not they differ from the reference. Two consequences matter for ancestry analysis: - **A VCF names a reference build.** Most whole-genome providers deliver against **GRCh38**; most ancient-DNA reference panels — including the Allen Ancient DNA Resource — are on **GRCh37**. The same variant has different coordinates on each, so the file must be lifted from one to the other before it can be merged. - **A VCF only lists differences.** Positions where you match the reference may be absent, which means "reference genotype" and "no data" have to be told apart carefully during conversion. ## How the upload works Whole-genome upload is a €10 add-on on two of our analyses, [Ancient Ancestry](/qpadm) (our qpAdm analysis) and [Ancient Matches](/ancient-matches), and accepts `.vcf` or `.vcf.gz` up to 1 GB. At upload: 1. The file is read once and **converted to the reference panel's markers** — the roughly 1.2 million positions the ancient panel is genotyped at. Everything else in the VCF is discarded; an ancient-DNA analysis cannot use positions the ancient samples were never read at. 2. Coordinates are **lifted from GRCh38 to GRCh37** where the file declares GRCh38. 3. The converted genotype set is what the analysis runs on. **The VCF itself is not stored.** The result is a genotype file in the same shape a chip export produces — which is why everything downstream, from the merge to the report, is identical. The vendor-agnostic detail on what the pipeline detects and refuses is in the free [Raw DNA File Check](/lab/file-check), which is the one place a VCF can be checked without ordering anything. ## What changes versus a chip export This is the honest part, and it is less dramatic than whole-genome marketing suggests. **Coverage of the panel goes up — moderately.** A chip export overlaps the ancient panel at a few hundred thousand positions, depending on the chip. A whole-genome VCF can cover nearly all of the panel's markers, because it read everywhere. More overlapping markers means more f-statistics computed from more data, which means **smaller standard errors** on the qpAdm weights — and standard error is the number that bounds what a model can resolve. A file that could only support a two-way model at SE 0.09 may support a three-way model at SE 0.05. **Nothing else changes.** The reference panel is the same ancient individuals; the model is composed the same way; the p-value tests the same thing. A VCF does not unlock different sources, a different era or a different product. It is a denser measurement of the same genome. **Ancient Matches benefits most.** Segment matching against individual ancient genomes is limited by how many informative markers fall inside each shared stretch. A denser file resolves shorter segments and reports marker density on every row — see [Ancient DNA matches explained](/blog/ancient-dna-matches-ibs-explained) for what those segments mean and do not mean. ## Things that go wrong - **Low-pass sequencing.** Some "whole-genome" products are sequenced at low depth and imputed — the genotypes are statistical guesses at many positions. They still convert, but the standard errors reflect the imputation, not the sequencing. - **Missing chromosomes.** Some providers deliver autosomes only; the Y and mitochondrial chromosomes may be absent, which means the paternal and maternal haplogroup add-ons cannot be run from that file. The File Check reports row counts per chromosome class so you know before you pay. - **Wrong build declared.** A VCF that says GRCh37 but is on GRCh38 will merge at the wrong positions and produce a genome that looks like nobody. The converter reads the header; if the header is wrong, the result is wrong. - **Files over 1 GB.** Some providers ship uncompressed VCFs of several gigabytes. Compress to `.vcf.gz` first; if it is still over the limit, the file likely contains non-variant records that can be stripped with standard tools. ## Provider notes The three providers we see most often deliver slightly different things, and the differences matter at upload: - **Nebula Genomics** delivers a whole-genome VCF on GRCh38 as `.vcf.gz`, typically well under the 1 GB limit; deep-coverage products convert cleanly, low-pass products convert with the imputation caveat above. - **Dante Labs** delivers a large VCF set, sometimes split into SNP and indel files; the SNP file is the one to upload, and it is usually on GRCh38 for recent orders and GRCh37 for older ones — check the header. - **tellmeGen** whole-genome orders deliver a VCF alongside the chip-style raw export; either works, and the VCF is the denser of the two. In every case the free File Check will state the detected build, the row counts per chromosome class and a verdict per analysis before you commit a euro. ## Which analyses accept it | Analysis | Whole-genome VCF | Chip export | |---|---|---| | [Ancient Ancestry](/qpadm) (qpAdm) | yes, €10 add-on | yes | | [Ancient Matches](/ancient-matches) | yes, €10 add-on | yes | | [Ancestry Map](/g25) (Global25) | no — coordinates come from the Eurogenes service | no — same | | [Raw DNA File Check](/lab/file-check) | yes, free | yes, free | Global25 is the odd one out because no one but the independent Eurogenes service produces G25 coordinates, and their input rules are their own — see [How to get your Global25 coordinates](/blog/how-to-get-global25-coordinates). ## What a whole genome does not buy It does not buy certainty about ancestry. Standard errors shrink; the dependence of every weight on which sources and outgroups were chosen does not. A whole-genome qpAdm model still has to clear the same bar as a chip one, still has to be read in the order set out in [How to read qpAdm results](/blog/how-to-read-qpadm-p-value-z-score-standard-error), and still never names anyone as an ancestor. What it buys is a denser file — which, for a method whose limiting quantity is coverage, is exactly the right thing to buy, and the report's model record shows it directly: the merged SNP count, the minimum SNP count per f4 statistic and the width of every source's 95% confidence interval. The [Ancient Ancestry page](/qpadm) covers the rest, and the terms are in the [glossary](/glossary). ## References - Danecek, P. et al. (2011). The variant call format and VCFtools. *Bioinformatics*, 27(15), 2156–2158. - Mallick, S. et al. (2024). The Allen Ancient DNA Resource (AADR): a curated compendium of ancient human genomes. *Scientific Data*, 11, 182. - Harney, É., Patterson, N., Reich, D. & Wakeley, J. (2021). Assessing the performance of qpAdm: a statistical tool for studying population admixture. *Genetics*, 217(4), iyaa045.