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Whole-genome sequencing data offer insights into human demography
Jonathan K Pritchard
Two new studies take distinct population genetic approaches to analyzing whole-genome sequencing data sets in order to estimate human demographic parameters. These papers refine our understanding of the relationships among human populations while illustrating both the possibilities and the statistical challenges of fitting demographic models to whole-genome data sets.
These are exciting times for human population genetics, as the ever-increasing number of human genome sequences promise to add greatly to our understanding of the evolution of modern humans1. The new genome sequence data will also shed light on other long-standing evolutionary questions such as the extent of recent human adaptation2. However, the availability of these large-scale data sets raises statistical and computational challenges. On page 1031 of this issue, Adam Siepel and colleagues3 report new statistical methods to estimate the relationships among populations from whole-genome sequence data of multiple individuals. In a related paper, Li et al. report a different new method for historical inference, but using one genome sequence at a time. Both papers represent important methodological advances in their ability to estimate detailed demographic information from whole-genome sequences. These studies refine several key aspects in human demographic models, including the timing of the population split between Africans and non-Africans.
This is starting to get interesting on his approach. Here is a PDF paper on his work that is attached file.
This is a link to his software that is available for free.
Jonathan K Pritchard
Two new studies take distinct population genetic approaches to analyzing whole-genome sequencing data sets in order to estimate human demographic parameters. These papers refine our understanding of the relationships among human populations while illustrating both the possibilities and the statistical challenges of fitting demographic models to whole-genome data sets.
These are exciting times for human population genetics, as the ever-increasing number of human genome sequences promise to add greatly to our understanding of the evolution of modern humans1. The new genome sequence data will also shed light on other long-standing evolutionary questions such as the extent of recent human adaptation2. However, the availability of these large-scale data sets raises statistical and computational challenges. On page 1031 of this issue, Adam Siepel and colleagues3 report new statistical methods to estimate the relationships among populations from whole-genome sequence data of multiple individuals. In a related paper, Li et al. report a different new method for historical inference, but using one genome sequence at a time. Both papers represent important methodological advances in their ability to estimate detailed demographic information from whole-genome sequences. These studies refine several key aspects in human demographic models, including the timing of the population split between Africans and non-Africans.
This is starting to get interesting on his approach. Here is a PDF paper on his work that is attached file.
This is a link to his software that is available for free.