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Welcome to the free public server for detecting signatures of positive and negative selection from coding sequence alignments using state-of-the-art statistical models. This service is brought to you by the viral evolution group at School Of Medicine of the University of California, San Diego. Over its lifetime Datamonkey.org has processed 74575 analyses at a rate of 121.133 jobs/day (over the last 30 days).

Datamonkey.org can help you answer the following questions ( publications citing datamonkey.org) :

Which codon sites are under positive or negative selection?

Three different codon-based maximum likelihood methods, SLAC, FEL and REL, can be used estimate the dN/dS (also known as Ka/Ks or ω) ratio at every codon in the alignment. An exhaustive discussion of each approach can be found in the methodology paper. All methods can also take recombination into account. This is done by screening the sequences for recombination breakpoints, identifying non-recombinant regions GARD tool and allowing each to have its own phylogentic tree.

Is there evidence of selection in my alignment?

The PARRIS method, developed by Konrad Scheffler and colleagues, extends traditional codon-based likelihood ratio tests to detect if a proportion of sites in the alignment evolve with dN/dS>1. The method takes recombination and synonymous rate variation into account.

Which codon sites are under positive or negative selection at the population level?

The codon-based maximum likelihood IFEL method can investigate whether sequences sampled from a population (e.g. viral sequences from different hosts) have been subject to selective pressure at the population level (i.e. along internal branches). A discussion of the method and its application can be found here

Did selective pressure vary along lineages, i.e. over time?

The codon-based genetic algorithm GABranch method can automatically partition all branches of the phylogeny describing non-recombinant data into groups according to dN/dS. Robust multi-model inference is used to collate results from all models examined during the run to provide confidence intervals on dN/dS for each branch and guard against model misspecification and overfitting (method details).

Did any sites co-evolve?

A Bayesian graphical model is deduced from reconstructed substitutions at each branch/site combination to infer conditional evolutionary dependancies of sites in the alignments, i.e. whether a site is more or less likely to experience a non-synonymous substitution at a branch when certain other sites do (or do not) experience non-synonymous substitutions at the same branch. The method was introduced in the evolutionary context in our paper on the evolution of the phenotypically important and highly variable V3 loop of the envelope glycoprotein in HIV-1.

Has recombination acted upon sequences in an alignment?

Recombination leaves an imprint on sequence alignments: different segments of the alignment may be described by different phylogenetic trees, called phylogenetic discordance. Datamonkey.org implementes two methods: SBP, suitable for answering the question "Is there evidence of recombination in the alignment?", and GARD, that attempts to find all the recombination breakpoints. Both method are described in this paper. The output of GARD is accepted by most other analyses, and because recombination can mislead phylogenetic analysis that do not account for it, we strongly urge that recombination testing be done on any alignment that is going to be analyzed for positive selection.

You can also submit a collection of HIV-1 sequences for recombination screening by a specialized recombination detection algorithm SCUEAL.