Vanilla 1.2 (April 15, 2001)

http://users.ox.ac.uk/~strimmer/vanilla/

Copyright (c) 1999-2001 Korbinian Strimmer
This package may be distributed under the terms of the GNU General Public License

Overview:

Vanilla is a collection of command line programs written in Java to access some selected features in PAL, a Java library for molecular evolution and phylogenetics (see http://www.pal-project.org for details on PAL). Note that Vanilla does not provide all functionality available in PAL.

In fact, for the vast majority of things you still need to program yourself! In that respect, this package is provided in the hope that it may serve as a useful guide and introduction to learn how to use PAL in your own programs.

Vanilla 1.2 is only a minor update from Vanilla 1.1 to accommodate the changes from PAL 1.1 to PAL 1.2. It runs best in a shell environment (Unix, Windows, MacOS X) and requires Java 1.1 or better (see Download and Installation section).

Vanilla includes programs to compute maximum-likelihood distances for nucleotides and amino acid data, to estimate of maximum-likelihood branch lengths on trees (incl. clock trees and dated tips), for statistical (e.g., Shimodaira-Hasegawa) and topological (Robinson-Foulds) comparison of trees, to infer demographic parameters from trees (based on the coalescent), and also utility programs to reformat and modify alignments.

If you wish to cite this package please use a phrase like "the Vanilla 1.2 frontend to PAL 1.2", or similar, and refer to

Drummond, A., and K. Strimmer. 2001. PAL: An object-oriented programming library for molecular evolution and phylogenetics. Bioinformatics in press.

Applications:

Vanilla applications offer plain and simple text-only interfaces and are intended to be run in a shell environment. Be warned - there is no graphical user interface, Vanilla is definitely not Mac/Windows-like.

Applications with a PHYLIP-style character user interface (self-explanatory menus):

• MLDIST:

GENERAL OPTIONS
 d                   Sequence data type?  Nucleotides
 e            Estimate model parameters?  No
 k     Compute observed or ML distances?  ML distances
SUBSTITUTION MODEL
 m                Model of substitution?  F84 (Felsenstein 1984, PHYLIP)
 t               PHYLIP Ts/Tv parameter?  1.1 (expected Ts/Tv ratio)
 f               Nucleotide frequencies?  As observed in data set
 w          Model of rate heterogeneity?  Uniform rate
 
Quit [q], confirm [y], or change [menu] settings:

Computes pairwise maximum-likelihood distance matrices for nucleotide, amino acid, and two-state data under a variety of substitution models (GTR,TN, HKY, F84, F81, JC; Dayhoff, JTT, MTREV24, BLOSUM, VT, WAG, CPREV) and in incorporating rate variation over sites (uniform rate or discrete Gamma model). MLDIST also computes observed distances and can obtain approximate estimates of unknown model parameters, e.g, the Ts/Tv ratio. The default file name for the sequences is "indata" (PHYLIP or CLUSTAL W format).
• MLTREE:

GENERAL OPTIONS
 d                   Sequence data type?  Nucleotides
 e            Estimate model parameters?  No
 o              Optimize branch lengths?  Yes
 b           Branch lengths constraints?  Clock-like tree with dated tips
 i       Write out site log-likelihoods?  No
 x                 Tree comparison test?  None
SUBSTITUTION MODEL
 m                Model of substitution?  F84 (Felsenstein 1984, PHYLIP)
 t               PHYLIP Ts/Tv parameter?  2.0 (expected Ts/Tv ratio)
 f               Nucleotide frequencies?  As observed in data set
 w          Model of rate heterogeneity?  Uniform rate
 
Quit [q], confirm [y], or change [menu] settings:

Computes likelihoods of trees (in "intree") under a variety of substitution models (see MLDIST). The likelihood can be computed using the user-provided branch lengths or, alternatively, branch lengths can be optimized as well (for unconstrained trees, clock trees, and clock trees with dated tips). If more than one tree is present in an "intree" file the trees can be statistically compared (using the Kishino-Hasegawa, Shimadoira-Hasegawa, and expected Akaike weights). Note, however, that MLTREE presently does not do any tree searches.
• EVOLVE:

GENERAL OPTIONS
 d                   Sequence data type?  Nucleotides
 n           Number of output data sets?  1
 s                      Number of sites?  1000
SUBSTITUTION MODEL
 m                Model of substitution?  F84 (Felsenstein 1984, PHYLIP)
 t               PHYLIP Ts/Tv parameter?  1.1 (expected Ts/Tv ratio)
 f               Nucleotide frequencies?  Not yet specified
 w          Model of rate heterogeneity?  Uniform rate
 
Quit [q], confirm [y], or change [menu] settings:

Generates artificial data sets for a tree (in "intree") and a model of sequence evolution (available models are the same as in MLTREE and MLDIST).
• DISTTREE:

GENERAL OPTIONS
 u                Reconstruction method?  Least-squares (on user trees)
 o              Optimise branch lengths?  Yes
 b           Branch lengths constraints?  None
 l                  Chi-square distance?  Weighted (Fitch-Margoliash 1967)
 
Quit [q], confirm [y], or change [menu] settings:

Tree methods dealing with distance matrices ("indist"). If user specified tree topologies (in "intree") are available, weighted and unweighted LS branch lengths (for unconstrained trees, clock trees, and clock trees with dated tips) can be estimated. In addition, NJ and UPGMA trees can be computed from the distance matrix.
• REWRITE:

GENERAL OPTIONS
 v               Sequence output format?  PHYLIP Interleaved
 g            Drop gaps from input data?  No
 z       Constant/non-informative sites?  Keep sites                            
 j                Jumble sequence order?  No
 h                      Bootstrap sites?  No
 n           Number of output data sets?  1
 
Quit [q], confirm [y], or change [menu] settings:

Reads a data set (in "indata") and reformats it into various formats (PHYLIP Sequential, Interleaved, Plain, Clustal W). Also removes sites with gaps, removes constant and non-informative sites, jumbles sequence order, and produces bootstrapped data sets.

To get a list of available options simply call the program without any parameter. On a Macintosh you will be asked to enter the command line parameters.

• TREECOMP:

Usage: treecomp intree1 intree2

Reads two trees, each from a different file, and computes the Robinson Foulds score (topological distance measure based on splits). If the two trees are identical a score of zero is returned.
• DEMOGRAPH:

Usage: demograph intree [epsilon] outfile

Estimates demographic parameters (effective population size, growth rate) by maximizing the coalescent prior for a single given clocklike tree. Also computes the classic skyline plot, a non-parametric estimate of population size through time (O. G. Pybus et al. 2000. Genetics 155:1429-1437), and its extension, the generalized skyline plot (K. Strimmer and O. G. Pybus. 2001. Submitted). Epsilon is the smoothing parameter of the generalized skyline plot.
• CONCAT:

Usage: concat infile1 infile2 .. outfile

Concatenates a set of sequence alignments.
• SHOWTREE:

Usage: showtree treefile [outfile]

Reads treefile (NH format), generates ASCII picture, and computes distance matrix induced by branch length. If no outfile is specified the ASCII picture of the tree is printed to stdout.
• REROOT:

Usage: reroot node treefile outfile

Reads a treefile (NH format) and reroots the tree, making node the new root.
• SPLITCODON:

Usage: splitcodon infile outfile

Separate 1st, 2nd, 3rd codon positions of an alignment into separate file.

Hint: In many shell environments typing "v_" followed by a tab will provide you with a list of all Vanilla applications.

Download and Installation:

Vanilla requires Java 1.1 (or better). It is strongly recommended to install a Java Virtual Machine with a JIT ("just in time") compiler. On Linux installation of Sun Java 1.3 for Linux is recommend because it includes a very fast runtime system (based on a so-called hot-spot compiler). On the Macintosh please install a recent version of the Macintosh Runtime for Java (MRJ). However, probably the best way to run Vanilla on a Mac is to install MacOS X and then install the UNIX version.

This version of Vanilla relies on PAL 1.2. PAL is (c) 1999-2001 by the PAL Core Development Team and is licensed under the GNU General Public License. Sources and documentation for PAL are separately available from the PAL web page at http://www.pal-project.org.

Note that a Java compiler and download of PAL sources is not necessary as the Vanilla package already contains all necessary classes in precompiled form.

Vanilla 1.2 is distributed in two variants (for convenience only, functionality and sources are 100% identical across platforms):

• vanilla-1.2.tar.gz (Unix)
• vanilla-1.2.zip (Windows)

Due to the arrival of Mac OS X (=Unix), a separate Macintosh version is no longer supported.

After uncompressing using appropriate tools the following simple directory structure will be created on all platforms:

                 vanilla-1.2
              _______|______ _____ ______ __________
             |              |     |      |          |                
            bin           data   doc   classes     src        
         ____|____                       |          
        |    |    |                 vanilla.zip   
      unix  win  mac                   pal.zip

To be able to run the Vanilla programs the system needs to be told where the binaries and the Java bytecode sit on the hard drive. On Unix and Windows this is done by setting the PATH and CLASSPATH variables appropriately, on a Mac the Java classes need to be put in a special directory. In doubt please ask your local Unix/Windows/Mac expert for help:

• Unix (edit files .login, .cshrc, .bashrc):

%csh
setenv VDIR $HOME/vanilla-1.2
setenv PATH $VDIR/bin/unix:$PATH
setenv CLASSPATH $VDIR/classes/vanilla.zip:$VDIR/classes/pal.zip:$CLASSPATH

%sh, bash
VDIR=$HOME/vanilla-1.2
export PATH=$VDIR/bin/unix:$PATH
export CLASSPATH=$VDIR/classes/vanilla.zip:$VDIR/classes/pal.zip:$CLASSPATH


• Windows (edit autoexec.bat):

PATH C:\VANILLA-1.2\BIN\WIN
set CLASSPATH=C:\VANILLA-1.2\CLASSES\VANILLA.ZIP;C:\VANILLA-1.2\CLASSES\PAL.ZIP

• Macintosh:

Move the files vanilla.zip and pal.zip from the "classes" folder (in the Vanilla directory) into the "MRJ Classes" folder which sits in the "MRJ Libraries" directory which itself is located in the extensions folder of the System folder.

Vanilla can also be compiled into native code (as can PAL) using the GNU gcj compiler, makefiles are included with the distributions of both Vanilla and PAL.

Acknowledgments:

I thank Oliver Pybus and Andrew Rambaut for discussion. The name Vanilla was suggested by Alexei Drummond. The prefixing trick (application names) is due to Catherine Letondal. This work is supported by an Emmy-Noether-Fellowship of the DFG to K.S.