Computer software

Tutorials for Windows and MAC OSX/Linux/Unix command line

The best way of running the programs here is by the command line. Since some modern students have never seen the command line, I have written some notes to introduce the basics. I suggest that you go through the tutorial yourself before trying to run the programs like paml or bpp. I think the tutorial should take less than one hour. Please let me know if you find the tutorial confusing or if you have comments or suggestions.
Tutorial for Microsoft Windows command line, pdf, 4 pages
Tutorial for MAC OSX/Linux/Unix command line, pdf, 4 pages
An fairly extensive Introduction to Unix commands, written by Tim Massingham for the Workshop on Computational Molecular Evolution (CoME), pdf, 28 pages.

Phylogenetic analysis by maximum likelihood (PAML)

Yang, Z. 1997 PAML: a program package for phylogenetic analysis by maximum likelihood. Comput. Appl. Biosci. 13, 555-556.
Yang, Z. 2007 PAML 4: Phylogenetic Analysis by Maximum Likelihood. Mol. Biol. Evol. 24, 1586-1591.

BP&P: Bayesian analysis of genomic sequence data under the multispecies coalescent model

The program BP&P (bpp3.1.tgz) implements a series of Bayesian inference methods under the multispecies coalescent model. The analyses may include estimation of population size (theta's) and species divergence times (tau's), species tree estimation and species delimitation. Windows executables and C source code (for unix/linux/macosx) are all in the same archive. Here is a pre-compiled version for mac osx 7 and later (bpp3.1.macosx.tgz). Please read the documentation before you use this program. The following paper includes a tutorial for bpp 3.1.

Yang, Z. 2015. A tutorial of BPP for species tree estimation and species delimitation. Curr. Zool. pdf

BP&P replaces the old program MCMCcoal, which implements the Bayesian method of Rannala & Yang (2003) and Burgess & Yang (2008). A mac OSX version is here (bpp2.2-mac-x86_64.tar.gz) for 64-bit intel chips (sorry this is an old version).

Bo Xu has written a graphics user interface for BPP, called bppX. The compiled executables are here for Windows, Mac OSX, and linux. You install (unpack and compile) the current version of bpp first. Then unpack the GUI bppX. Then go to Function-Configuration to specify the folder name for the bpp files. Questions and discussions about bp&p should go to this link.

  Source code  bppX1.2.2-src.tgz
  Windows  bppX1.2.2+bpp3.1-win-x86.tgz
  Mac OSX  bppX1.2.2+bpp3.1-osx-x86_64.dmg
  Linux(coming soon)

3s

The program 3s implements likelihood ratio tests to test for gene flow between two closely related species. Click on the link above for more information.

MrBayes 3.2.1 with Dirichlet priors on branch lengths

The archive name is mb3.2.1.Dir.tgz. This is a modified version of MrBayes Version 3.2.1, modified to use the Gamma-Dirichlet and Inverse Gamma-Dirichlet priors for branch lengths (Rannala et al. in press; Zhang et al. 2012). This also includes the two exponential priors on internal and external branch lengths described by Yang & Rannala (2005) and Yang (2007). There is a brief description of the changes in the file mb3.2.Dirichlet.Notes.pdf inside the archive. If you use the modified program, please cite MrBayes as well as the papers that describe the modifications.

Yang, Z 2007 Fair-balance paradox, star-tree paradox and Bayesian phylogenetics. Mol. Biol. Evol. 24, 1639-1655.
Yang, Z & Rannala, B. 2005 Branch-length prior influences Bayesian posterior probability of phylogeny. Syst. Biol. 54, 455-470.
Rannala, B., T. Zhu, and Z. Yang. 2012. Tail paradox, partial identifiability and influential priors in Bayesian branch length inference. Mol. Biol. Evol. 29:325-335.
Zhang, C., B. Rannala, and Z. Yang. 2012. Robustness of compound Dirichlet priors for Bayesian inference of branch lengths. Syst. Biol. 61:779-784.

oncoSpectrum v1.2: ML program for estimating mutation rates using cancer mutation databases.

Yang Z, Ro S, Rannala B. 2003. Likelihood models of somatic mutation and codon substitution in cancer genes. Genetics 165:695-705.


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