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Populations in statistical genetics: what are they, and how can we infer them from whole genome data?

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Describing the genetic structure within a species using the intuitive concept of a population has been a very successful approach throughout the history of biology. However, now that whole genome sequencing is becoming available, our ability to distinguish the detailed relationships between individuals makes classifying them into populations seem crude. Conversely, populations are a useful simplification tool for describing historical demography in a conceptually useful manner. I will describe a model of evolution in which populations exist as a unit, but individuals may still have complex relationships. Evolutionary history can be understood as the history of populations, and can be described in principle by complex demographic models. This work uses and extends the FineSTRUCTURE modelling framework (Lawson et al 2012 PLoS Genetics) to describe population history as a series of drift events that can be shared between individuals to varying degrees. Careful modelling allows a separation of the interesting population level drift from recent relatedness which is not part of any species-level genetic signal.

This talk is part of the Populations in Statistical genetics series.

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