Approximating the coalescence process with recombination as a Markov model along sequences—an approach called the Sequential Markov Coalescent or SMC—greatly reduces the complexity of modelling sequences. Rather than modelling the full joint probability of all nucleotides it suffices to model the probability of pairs of neighbouring nucleotides. Combined with hidden Markov models, SMC has been used to develop a number of different inference models in recent years, capable of drawing inference from full genomic sequence alignments.

I will give a short overview of the different methods based on SMC, then talk about a number of models we have developed in Aarhus and how we have used these methods to analyse the genetics of ancestral species, especially the great apes.