News
- 31/05/18 Version 1.5.5 there.
- 27/04/15 Version 1.5.2 finally there.
- 18/04/15 Migrating from Gna! to Github.
Description
With the CoMap package, you can perform the following tasks:
- Compute probabilistic substitution maps, possibly with biochemical weights (comap)
- Compute coevolution statistics (correlation, compensation) for all pairs of sites (comap)
- Test for significance of pairwise statistics using parametric bootstrap (comap)
- Cluster sites according to a coevolution distance (correlation, compensation) (comap)
- Test for significance of groups using parametric bootstrap (comap + R script)
- Perform correction for multiple testing with group statistics (R script)
- Test if given candidate groups of sites are significantly coevolving (comap)
- Compute mutual information (MI) based statistics for all pairs of sites (mica)
- Test significance of MI statistics using various methods (mica)
- Advanced test of significance of MI statistics, accounting for site-specific substitution rates (mica + R script)
Getting CoMap
The CoMap package can be compiled from source, or installed from packages for various Linux Systems (including Ubuntu, Fedora, Suse). Standalone binary executables are also available for Linux (32 and 64 bits). On MacOSX, CoMap is available via Homebrew. More information can be found on the wiki.
Documentation
The documentation of the program can be browsed here. A PDF version of the manual can be downloaded from here.
Example data sets are distributed along with the source code. The 'simple' analyses example contain the minimal set of options required. For more advanced usage, the user can look at the example analyses from the 2007 paper. All examples are updated as the program options change.
Citation
Cite the following article if you use the pairwise method:
Dutheil J, Pupko T, Jean-Marie A, Galtier N. A model-based approach for detecting coevolving positions in a molecule. Mol Biol Evol. 2005 Sep;22(9):1919-28.
Cite the following article if you use the clustering method:
Dutheil J, Galtier N. Detecting groups of co-evolving positions in a molecule: a clustering approach. BMC Evol Biol. 2007 Nov 30;7(1):242
Cite the following article if you use the candidate approach method:
Dutheil JY, Jossinet F, Westhof E. Base pairing constraints drive structural epistasis in ribosomal RNA sequences. Mol Biol Evol. 2010 Aug;27(8):1868-76
MICA and the new p-value computation algorithm are described in:
Dutheil JY. Detecting coevolving positions in a molecule: why and how to account for phylogeny. Brief Bioinform. 2011 Sep 24.