The purpose of this software is to generate a transition model showing the
mutational pathways of drug resistance for viruses under drug pressure. The
input to the program is a set of aligned DNA fasta files (of the same
sequence length), one per patient, for
patients under a specific therapy X. Each fasta file should be labeled
by the patient number. Each fasta file must contain serially-sampled
viral clonal sequences labeled with a sequence ID containing the sampling time as a
prefix (format "Time.uniqueID"
with Time a three digit number
with leading zeros). The unit time (weeks, days, months) is not required
for the program but needs to be the same for
the model to be correct. The program also requires a “markers” file containing the positions
and amino acids associated with drug resistance for therapy X.
The output of the program is a list of observed transitions between different viral genotypes for a particular time interval and their transition probabilities and\or a graph (if GraphViz was installed) showing the transition model. Other output options that generate statistics of the model are also available.
The settings of the program can be controlled via the sample_variables.txt file or through the GUI.
Installation, user manual and sample files are included in the vPhyloMM tar file.
Detailed installation steps for Windows and UNIX/LINUX are included under the 'Documentation/Installation' directory. Note that to use the GUI, the user will need to install ActiveState's ActivePerl (http://www.activestate.com/activeperl) distribution as the standard distribution is not compatible with Tcl/Tk.
The creation of graphs requires the additional installation of GraphViz and the GraphViz perl module. These are optional if vPhyloMM is not going to be used to graph transition states.
To read more about how to use vPhyloMM go to http://vphylomm.sourceforge.net/
You may also run:
perldoc Run_vPhyloMM.pl
To get started using vPhyloMM try:
perl Run_vPhyloMM.pl --variables-file=sample-variables.txt --gui
Buendia, P., Cadwallader, B. and DeGruttola, V. (2009) A phylogenetic and Markov model approach for the reconstruction of mutational pathways of drug resistance. Bioinformatics, In Press.