Extensively Parameterized Mutation-Selection Models Reliably Capture Site-Specific Selective Constraint.

ABSTRACT: The mutation-selection model of coding sequence evolution has received renewed attention for its use in estimating site-specific amino acid propensities and selection coefficient distributions. Two computationally tractable mutation-selection inference frameworks have been introduced: One framework employs a fixed-effects, highly parameterized maximum likelihood approach, whereas the other employs a random-effects Bayesian Dirichlet Process approach. While both implementations follow the same model, they appear to make distinct predictions about the distribution of selection coefficients. The fixed-effects framework estimates a large proportion of highly deleterious substitutions, whereas the random-effects framework estimates that all substitutions are either nearly neutral or weakly dele

SUBMITTER: Spielman SJ 

PROVIDER: S-EPMC5062325 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature