The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.
Journal article
2022-02-01T00:00:00+00:00
375
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Chromosomes, Human, Pair 20, Humans, Statistics, Nonparametric, Pedigree, Sequence Analysis, DNA, Genetics, Population, Genomics, Evolution, Molecular, Haplotypes, Mutation, Genome, Human, Geography, Computer Simulation, Databases, Nucleic Acid, Africa, Genetic Variation, Spatio-Temporal Analysis, Human Migration, Datasets as Topic, DNA, Ancient