A nonparametric HMM for genetic imputation and coalescent inference

Genetic sequence data are well described by hidden Markov models (HMMs) in which latent states correspond to clusters of similar mutation patterns. Theory from statistical genetics suggests that these HMMs are nonhomogeneous (their transition probabilities vary along the chromosome) and have large s...

Полное описание

Библиографические подробности
Главные авторы: Elliott, L, Teh, Y
Формат: Journal article
Опубликовано: Institute of Mathematical Statistics 2016