group/reference’ populations are older than, or at least contemporary 
with, the target genome or group that we are trying to model18. However, 
this has been challenging, due to the limited statistical power offered 
by the thousands-fold lower sample sizes and reduced sequence qual-
ity of ancient genomes.
Reconstructing genetic histories and ancestry models from ancient 
DNA (aDNA) data commonly uses methods based on f-statistics13,19–22. 
Their popularity is rooted in a number of favourable properties, such 
as enabling analyses of lower-quality aDNA data, relative robustness 
to ascertainment and theoretical guarantees of unbiasedness, includ-
ing in the presence of population bottlenecks21,23. Approaches derived 
from f-statistics, such as qpAdm13, are close to unique in enabling the 
unbiased fitting of admixture models, including identifying the num-
ber of such events and the closest representatives of sources 13,14,23. 
However, f-statistics have not always had sufficient power to recon-
struct events that involve closely related ancestries, despite increas-
ing sample sizes 6,24. Methods that identify haplotypes, or shared 
segments of DNA that are not broken down by recombination, have 
previously been shown to have more power than those using individual 
https://doi.org/10.1038/s41586-024-08275-2
Received: 14 December 2023
Accepted: 23 October 2024
Published online: 1 January 2025
Open access
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1Ancient Genomics Laboratory, Francis Crick Institute, London, UK. 2Genetics Institute, University College London, London, UK. 3iTHEMS, RIKEN, Wako, Japan. 4Department of Archaeology and 
Ancient History, Uppsala University, Uppsala, Sweden. 5Bioinformatics and Biostatistics, Francis Crick Institute, London, UK. 6Centre for Palaeogenetics, Stockholm University, Stockholm, Sweden. 
7Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden. 8Department of History, King’s College London, London, UK. ✉e-mail: leo.speidel@riken.jp; 
pontus.skoglund@crick.ac.uk