Some collaborators and I are building an ancestral inference tool, and we're having trouble obtaining reliable ground-truth data for samples of mixed ancestry. All the ground-truth DNA datasets we're aware of (Thousand Genomes, Simons Foundation) are from persons reported as unequivocally belonging to some population (East Asian, African/African-American, South Asian, or even something specific like Somali, Icelandic or Cambodian.)

But we can't find any samples that are attestedly mixed-ancestry. We've thought about just generating simulated data using VCFs from two persons of different known ancestries, but we're not sure how to account for the non-random aspects of recombination, which are described here: https://www.bio-itworld.com/news/2019/03/06/latest-genetic-map-finds-recombination-is-not-so-random And we don't know of any tools that could perform this task for us.

Does anyone have suggestions for obtaining/simulating DNA data for persons of mixed ancestry? This is a natural enough problem that we suspect others must have encountered it also.


1 Answer 1


Price et al 2009 describe how to simulate admixed genomes in this paper.

We constructed 40 haploid admixed genomes (n = 1 to 40) from the 40 haploid Yoruba and 40 haploid French genomes by using haploid Yoruba genome n and haploid French genome n to construct admixed genome n, so that ancestral genomes were never reused. To construct an admixed genome, we began at the first marker on each chromosome and sampled French ancestry with probability α and Yoruba ancestry with probability 1-α. Ancestry was resampled based on an exponential distribution with weight λ (the number of generations since admixture) so that a new ancestry was sampled with probability 1−e−λg when traversing a genetic distance of g Morgans. Each time ancestry was resampled, we sampled French ancestry with probability α and Yoruba ancestry with probability 1-α. For each individual, we used a value of α to apply to the entire genome by sampling from a beta distribution with mean 0.20 and standard deviation 0.10 (typical for African Americans [4])

You could apply this method to e.g. .bam/.vcf files from SGDP and use the sampled ancestry as regions in the .bam/.vcf file from different ethnicities.


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