About SIMMAP 1.5
For information on Version 1.0, please go here.

SIMMAP 1.5 is a post tree analysis GUI software package for stochastically mapping mutations on phylogenies. This approach does not rely on parsimony and, therefore, does not suffer some of the serious drawbacks of that method. It uses the "indirect" mutational mapping approach as first developed by R. Nielsen (2002). The name SIMMAP is an acronym for StochastIc Mutational MApping on Phylogenies.

SIMMAP 1.5 implements stochastic mutational mapping using a wide range of models: 4 x 4 general reversible nucleotide models and standard Mk character models. SIMMAP 1.5 allows addressing a variety of evolutionary questions. Specifically, questions about the number, type and placement of mutations on a phylogeny. In addition, tests of character correlation, positive selection, and ancestral states are available.

SIMMAP 1.5 was written as a major update to version 1.0 (GUI) version written for Mac OS X (Bollback, 2006). This new incarnation deals with a number of long running bugs. In addition, the new version has been streamlined for ease of use and robustness. The result of these goals, is that the program has lost a number of features. It now focuses solely on generating and analyzing mutational maps.

Brief overview of features in version 1.5:

  1. A simplified data view that allows the user to make changes to the sequence names and the sequences.
  2. A redesigned tree view with all the available display options situated in a panel on the left of the tree (rather than using popup windows). In addition, enhanced drawing of the trees/mutational maps.
  3. Configuring the evolutionary substitution model has been simplified and is thus easier. For example, both nucleotide and standard model options are accessible through a single window.
  4. Standard characters can have an individual substitution model configured for each character. This alleviates the problem when performing character correlations and a prior for one character is not appropriate for the other character(s).
  5. Empirical priors are available for characters for more than two states, rather than requiring they have an equal frequency (1/k) prior.
  6. A much simplified analysis window.
  7. Other minor features.