A geographic history of human genetic ancestry

Describing the distribution of genetic variation across individuals is a fundamental goal of population genetics. We present a method that capitalizes on the rich genealogical information encoded in genomic tree sequences to infer the geographic locations of the shared ancestors of a sample of sequenced individuals. We use this method to infer the geographic history of genetic ancestry of a set of human genomes sampled from Europe, Asia, and Africa, accurately recovering major population movements on those continents. Our findings demonstrate the importance of defining the spatial-temporal context of genetic ancestry to describing human genetic variation and caution against the oversimplified interpretations of genetic data prevalent in contemporary discussions of race and ancestry., , , # A geographic history of human genetic ancestry

[https://doi.org/10.5061/dryad.p5hqbzkwz](https://doi.org/10.5061/dryad.p5hqbzkwz)

## Description of the data and file structure

Data and codes for testing and fitting GAIA

### Files and variables

#### File: data.tar.gz

**Description:** A gzip compressed archive with the following contents:

The `slim` directory contains simulation scripts and outputs for testing GAIA with the SLiM software in continuous and discrete geographic space. Each subdirectory corresponds to a different geographic space representation. The following subdirectories and files include:

* `continuous-space/` : Simulations on an abstract continuous plane
* `uniform-landscape/` : SLiM simulations with spatially homogeneous carrying capacity
* `gaussian-dispersal/` : simulations with a Gaussian dispersal kernel
* `analysis/`
* `performance.R, performance.sh` : R script and shell script used to run GAIA on each of the simulation tree sequences ...,