Which site(s) in an alignment evolve towards to or away from a particular residue.
Screen protein sequence alignments where the direction of evolution can be resolved (via tree rooting, e.g. using an outgroup) to find sites which evolve differently from a standard protein model (selected by the user), or a gene-average model (GTR) to find evidence of directional selection.
FFADE (FUBAR Approach to Directional Evolution) is a fast method to test whether or not a subset of sites in a protein alignment evolve towards a particular residue along a subset of branches at accelerated rates compared to reference model. FADE uses a random effects model and latent Dirichlet allocation (LDA) - inspired approximation methods to allocate sites to rate classes.
Note: the names of sequences in the alignment must match the names of the sequences in the tree.
A JSON file with analysis results (http://hyphy.org/resources/json-fields.pdf).
A custom visualization module for viewing these results is available (see http://vision.hyphy.org/FADE for an example)
--model The baseline substitution model to use [default] use GTR --branches Which branches should be tested for selection? All [default] : test all branches Internal : test only internal branches (suitable for intra-host pathogen evolution for example, where terminal branches may contain polymorphism data) Leaves: test only terminal (leaf) branches Unlabeled: if the Newick string is labeled using the {} notation, test only branches without explicit labels (see http://hyphy.org/tutorials/phylotree/) --grid The number of grid points Smaller : faster Larger : more precise posterior estimation but slower default value: 20 --method Inference method to use Variational-Bayes : 0-th order Variational Bayes approximation; fastest [default] Metropolis-Hastings : Full Metropolis-Hastings MCMC algorithm; orignal method [slowest] Collapsed-Gibbs : Collapsed Gibbs sampler [intermediate speed] --chains How many MCMC chains to run (does not apply to Variational-Bayes) default value: 5 --chain-length MCMC chain length (does not apply to Variational-Bayes) default value: 2,000,000 --burn-in MCMC chain burn in (does not apply to Variational-Bayes) default value: 1,000,000 --samples MCMC samples to draw (does not apply to Variational-Bayes) default value: 1,000 --concentration_parameter The concentration parameter of the Dirichlet prior default value: 0.5