bch441-work-abc-units/BIN-PHYLO-Tree_building.R
2017-11-01 23:30:01 -04:00

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R

# 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 <name>.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]