Inferring cultural transmission of reproductive success through machine learning methods

Project Summary

Cultural transmission of reproductive success has been observed in many human populations. This non-genetic transmission affects the genetic evolution of populations, yielding a decrease in genetic diversity and an increase of severe genetic diseases. The aim of this project is to develop methods based on Approximate Bayesian Computation and Machine Learning to infer this transmission from a sample of whole genomes, using simulated data as training sets. The intern will develop these methods and perform a cross-validation study on them. S/He will then apply the best methods to real data from the Saguenay Lac Saint-Jean in Quebec, where the occurrence of cultural transmission of reproductive success has already been shown using demographic data. The methods will then be applied to several populations from the 1000 Genome database with contrasted lifestyles (e.g. farmers and herders). This will allow, therefore, assessing the generality of cultural transmission of reproductive success in human populations.

Frédéric Austerlitz