# BIN-PHYLO-Tree_building.R # # Purpose: A Bioinformatics Course: # R code accompanying the BIN-PHYLO-Tree_building unit. # # Version: 1.0 # # Date: 2017 10. 31 # Author: Boris Steipe (boris.steipe@utoronto.ca) # # Versions: # 1.0 First 2017 version # 0.1 First code copied from 2016 material. # # # TODO: # Add MrBayes # https://cran.r-project.org/web/packages/phangorn/vignettes/IntertwiningTreesAndNetworks.html # # == DO NOT SIMPLY source() THIS FILE! ======================================= # # If there are portions you don't understand, use R's help system, Google for an # answer, or ask your instructor. Don't continue if you don't understand what's # going on. That's not how it works ... # # ============================================================================== #TOC> ========================================================================== #TOC> #TOC> Section Title Line #TOC> ------------------------------------------------------- #TOC> 1 Calculating Trees 43 #TOC> 1.1 PROMLPATH ... 64 #TOC> 1.1.1 ... on the Mac 69 #TOC> 1.1.2 ... on Windows 80 #TOC> 1.1.3 ... on Linux 94 #TOC> 1.1.4 Confirming PROMLPATH 99 #TOC> 1.2 Building a maxiiimum likelihood tree 108 #TOC> #TOC> ========================================================================== # = 1 Calculating Trees =================================================== # Follow the instructions found at phylip's home on the Web to install. If you # are on a Windows computer, take note of the installation directory. # After you have installed Phylip on your computer, install the R package that # provides an interface to the Phylip functions. if (!require(Rphylip, quietly=TRUE)) { install.packages("Rphylip") library(Rphylip) } # Package information: # library(help = Rphylip) # basic information # browseVignettes("Rphylip") # available vignettes # data(package = "Rphylip") # available datasets # This will install RPhylip, as well as its dependency, the package "ape". # == 1.1 PROMLPATH ... ===================================================== # The next part may be tricky. You will need to figure out where # on your computer Phylip has been installed and define the path # to the proml program that calculates a maximum-likelihood tree. # === 1.1.1 ... on the Mac # On the Mac, the standard installation places a phylip folder # in the /Applications directory. That folder contains all the # individual phylip programs as .app files. These are not # the actual executables, but "app" files are actually directories # that contain the required resources for a program to run. # The executable is in a subdirectory and you can point Rphylip # directly to that subdirectory to find the program it needs: # PROMLPATH <- "/Applications/phylip-3.695/exe/proml.app/Contents/MacOS" # === 1.1.2 ... on Windows # On Windows you need to know where the rograms have been installed, and you # need to specify a path that is correct for the Windows OS. Find the folder # that is named "exe", and right-click to inspect its properties. The path # should be listed among them. # If the path looks like "C:\Users\Meng\Programs\phylip-3.695\exe", then your # assignment has to be # PROMLPATH <- "C:/Users/Meng/Programs/phylip-3.695/exe" # (Note: "/", not "\") # I have heard that your path must not contain spaces, and it is prudent to # avoid other special characters as well. # === 1.1.3 ... on Linux # If you are running Linux I trust you know what to do. It's probably # something like # PROMLPATH <- "/usr/local/phylip-3.695/bin" # === 1.1.4 Confirming PROMLPATH # Confirm that the settings are right. PROMLPATH # returns the path list.dirs(PROMLPATH) # returns the directories in that path list.files(PROMLPATH) # lists the files [1] "proml" "proml.command" # If "proml" is NOT among the files that the last command returns, you # can't continue. Ask on the mailing list for advice. # == 1.2 Building a maxiiimum likelihood tree ============================== # Now read the mfa file you have saved in the BIB-PHYLO-Data_preparation unit, # as a "proseq" object with the read.protein() function of the RPhylip package: apsIn <- read.protein("APSESphyloSet.mfa") # ... and you are ready to build a tree. # There are many fast options in PHYLIP - we will use the most _accurate_ one # that it has: proml, a maximum-likelihood tree building program for protein # data. # Building maximum-likelihood trees can eat as much computer time # as you can throw at it. Calculating a tree of 48 APSES domains # with default parameters of Rproml() runs for more than half a day # on my computer. But we have only twelve sequences here, so the # process will take us about 5 to 10 minutes. Run this, and anjoy a good cup # of coffee while you are waiting. apsTree <- Rproml(apsIn, path=PROMLPATH) # A quick first look: plot(apsTree) # save your tree: save(apsTree, file = "APSEStreeRproml.RData") # If this did not work, ask for advice. # [END]