Fig 1. Hierarchical relationship of sequence contexts and key algorithmic elements of Baymer.

(A) Each mutation type is represented by a separate sequence context tree, related by the shared ‘mer’ level parameters and joint multinomial likelihood distribution. Each sequence context tree has a nested structure where information is partially pooled across each shared parent. (B) Polymorphism probabilities are parameterized as the product of the series of edges that lead to the sequence context of interest. (C) Sequence context trees are regularized using a spike-and-slab prior distribution.