We show that each member of a broad class of Markovian population models induces a unique stochastic process on the space of genealogies. We construct this genealogy process and derive exact expressions for the likelihood of an observed genealogy in terms of a filter equation, the structure of which is completely determined by the population model. We show that existing phylodynamic methods based on either the coalescent or the linear birth-death processes are special cases. We derive some properties of filter equations and describe a class of algorithms that can be used to numerically solve them. Our results open the door to statistically efficient likelihood-based phylodynamic inference for a much wider class of models than is currently possible.
Categories: q-bio.QM math.PR q-bio.PE stat.AP