FUBAR: a fast, unconstrained bayesian approximation for inferring selection.

@article{Murrell2013FUBARAF,
  title={FUBAR: a fast, unconstrained bayesian approximation for inferring selection.},
  author={B. Murrell and Sasha Moola and Amandla Mabona and Thomas Weighill and Daniel J. Sheward and Sergei L. Kosakovsky Pond and Konrad Scheffler},
  journal={Molecular biology and evolution},
  year={2013},
  volume={30 5},
  pages={
          1196-205
        }
}
Model-based analyses of natural selection often categorize sites into a relatively small number of site classes. Forcing each site to belong to one of these classes places unrealistic constraints on the distribution of selection parameters, which can result in misleading inference due to model misspecification. We present an approximate hierarchical Bayesian method using a Markov chain Monte Carlo (MCMC) routine that ensures robustness against model misspecification by averaging over a large… 

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References

SHOWING 1-10 OF 113 REFERENCES

A random effects branch-site model for detecting episodic diversifying selection.

Felsenstein's pruning algorithm is extended to allow efficient likelihood computations for models in which variation over branches (and not just sites) is described in the random effects likelihood framework, and this model treats the selective class of every branch at a particular site as an unobserved state that is chosen independently of that at any other branch.

A Bayesian model comparison approach to inferring positive selection.

The Bayesian approach outperforms the empirical Bayes method when the amount of sequence divergence is small and is less prone to false-positive inference when the sequences are saturated, while the results are indistinguishable for intermediate levels of sequences divergence.

Conjugate Gibbs Sampling for Bayesian Phylogenetic Models

The conjugate Gibbs formalism allows one to propose efficient implementations of complex models, for instance assuming site-specific substitution processes, that would not be accessible to standard MCMC methods.

Uniformization for sampling realizations of Markov processes: applications to Bayesian implementations of codon substitution models

A general method, based on a uniformization technique, which can be utilized to generate realizations of a Markovian substitution process conditional on an alignment of character states and a given tree topology is described.

Taking Variation of Evolutionary Rates Between Sites into Account in Inferring Phylogenies

A model based on population genetics is presented predicting how the rates of evolution might vary from locus to locus, and Markov chain Monte Carlo likelihood methods may be the only practical way to carry out computations for these models.

Not so different after all: a comparison of methods for detecting amino acid sites under selection.

Three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection are considered, suggesting that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effect models to allow for variation in synonymous substitution rates, and the naive application ofrandom effects models to extremely sparse data sets.

Maximum Likelihood Estimation on Large Phylogenies and Analysis of Adaptive Evolution in Human Influenza Virus A

Methods for obtaining approximate estimates of branch lengths for codon models are explored and the estimates were used to test for positive selection and to identify sites under selection in the viral gene under diversifying Darwinian selection.

A Dirichlet process model for detecting positive selection in protein-coding DNA sequences.

This work describes an approach to modeling variation in the nonsynonymous rate of substitution by using a Dirichlet process mixture model, which allows there to be a countably infinite number of nonsynonym rate classes and is very flexible in accommodating different potential distributions.

Detecting Amino Acid Sites Under Positive Selection and Purifying Selection

It is shown that the SLR method can be more powerful than currently published methods for detecting the location of positive selection, especially in difficult cases where the strength of selection is low.

Detecting Individual Sites Subject to Episodic Diversifying Selection

It is found that episodic selection is widespread and it is concluded that the number of sites experiencing positive selection may have been vastly underestimated.
...