Bayes Factor Cluster Analysis (BFCA) is a test of congruence among calibration hypotheses to assist their filtering prior to molecular clock analysis. It is a heuristic method based on the comparison of pairwise calibrations hypotheses by Bayes factors that allows identifying sets of congruent calibrations.
Installation (R package)
R >=3.0, R packages snow and snowfall
install.packages(c("snow", "snowfall"), dependencies=TRUE)
The following instructions assume that you downloaded the corresponding bfca file in your Downloads folder; replace username by your user name.
Type in an R session:
Mac OS X
To install the binary package (compiled in Snow Leopard 10.6.8), type in the R console:
If you have the Developer Tools installed, it is perhaps better to use the source package (or if you have problems installing the binary version). Type in the R console:
Type in the R console (assuming that you downloaded the bfca zip file in your Downloads folder; replace username by your user name):
BFCA tools 1.0.1
BFCA tools are a set of Perl scripts to help in the generation of xml input files required for the multiple runs of BEAST and the posterior processing of log files.
The only requirement is to have a Perl 5.8.x (or higher) interpreter installed. Most Linux distributions and Mac OS X have Perl installed by default. In Windows you can install any of the recommended distributions.
The scripts are distributed in a compressed tar file (bfca_tools_v1.01.tar.gz), so you will need to unpack and decompress them. On UNIX / UNIX-like environments execute:
tar xvfz bfca_tools_v1.tar.gz
In Windows you can use a tool such as 7-zip to do it.
This is a tutorial to run a Bayes Factor Cluster Analysis to evaluate the congruence of five calibration hypotheses with a gene simulated under a very simple model (strict clock; HKY; no rate heterogeneity; equal nucleotide frequencies).