Help is available in various places–

  • This tutorial (that you are reading now) is a tutorial introduction, but it is not a comprehensive reference. It skips a lot of detail.
  • The examples. The examples should have been installed along with the rest of p4, in a share directory. See the splash screen to find out where they are. Hopefully they work as advertised. Copy them to a working directory, and shake ‘em ‘til you break ‘em.
  • The class and module descriptions here. It should be fairly comprehensive and definitive.
  • Those descriptions mentioned in the previous point are also available in the Python help() and dir() functions. For example, try help(Alignment) from within p4 to read all the docstrings in the Alignment class.
  • Completion, for quick reminders. See Using interactive helpers.

P4 is used in Python – it is a Python package. You can import p4 into your Python as usual,

import p4

or (and I prefer this, but you might not) you can use the p4 script. The p4 script loads the package as:

from p4 import *

so all the p4 stuff goes to the ‘top level’ (which you may not like). The p4 script will read in files from the command line.

This week, p4 will recognize and read data files in the form of Nexus files, fasta files, Phylip (sequential or interleaved), GDE files (proper gde files only, not gde flat files), and clustalw aln files. P4 will recognize trees in Nexus and Phylip or raw Newick format. And of course p4 recognizes Python files. P4 understands Nexus data, taxa, characters, trees, and sets blocks, but it does not understand all the commands within those blocks.

Q: So why is it called p4?
A: Its an acronym- pppp
Q: So what’s it short for?
A: So its easy to type.

For the impatient

Here we provide a taster for some of the toolkit aspects of p4. These examples are very easy, and (except for the likelihood calculation) can be done using p4 interactively. You will probably find that for anything bigger writing a script would be easier.

These quickstart examples can be found in the Examples, in the A_quickStart directory. I suggest that you make a copy of the Examples, then change directory to A_quickStart in your copy, and then cd to directories therein. Be sure to read the files.

Draw a tree on the screen

Lets say you have a file that has a tree description in Newick or nexus format, and you want to draw that tree to the screen to see what it is. Say, to your shell:

p4 -d t.nex

(or whatever your file name is)

Convert between file formats

Lets say that you have an alignment in Phylip format and you want to convert it to nexus format. This is a small job, so we can use p4 interactively. First, read in the data, then give the alignment a name, and then tell the alignment to write itself in nexus format to a file

$ p4 data.phy                # Read the data at the command line
p4> a = var.alignments[0]    # Give the alignment a name
p4> a.writeNexus('data.nex') # Tell it to write itself to a file
p4>                          # Control-d to quit.

Extract a charset from an alignment

Lets say you have a multi-gene alignment, and you want to extract one of the genes and put it in an alignment file by itself. Here, the placement of the various genes in the alignment is defined in a nexus sets block, in this example in the file sets.nex. Do something like this:

$ p4 d.phy sets.nex                   # Read everything
p4> a=var.alignments[0]               # Name the alignment
p4> b = a.subsetUsingCharSet('gene1') # b is a new alignment
p4> b.writeNexus('gene1.nex')         # Tell b to write itself
p4>                                   # Quit with control-d

Tabulate the character frequencies in the data

$ p4 d.nex             # Read the data
p4> d=Data()           # Make a Data object
p4> d.compoSummary()   # Ask for a table of composition

Compare the topology of two trees

Lets say that you have two best trees from two different phylogenetic analyses using the same data. The trees might have the same topology, but the trees might not look much like each other, because they are rooted on different nodes, and many branches are rotated on their stems. However, ignoring branch lengths, the trees might still have the same topology, regardless of the various permutations. You can quickly find out how different they are, by doing something like the following:

$ p4 tree1.nex tree2.nex          # Read in both trees
p4> t1 = var.trees[0]             # Name the first one
p4> t2 = var.trees[1]             # Name the second one
p4> print t1.topologyDistance(t2) # Symmetric difference
0                                 # Zero means they are the same

The default metric for the topologyDistance() method is the symmetric difference, aka the unweighted Robinson-Foulds distance, which is the number of splits in one tree that are not in the other, plus the number of splits in the other tree that are not in the one. In this example, the trees are the same, and so the difference is zero. If the two trees had only one difference, the symmetric difference would be 2.

See also Tree.Tree.tvTopologyCompare()

A very simple likelihood calculation

This example is a bit more involved, and is not well suited to interactive use. The usual way to use p4 would be to make a script, and that is what we do here. Make a file with the following, and save it as

read(""" 2 2
t = var.trees[0] = Data()

Usually p4 scripts refer to other files for the data and the tree, but here it is all in the one script. Sequence data, a tree, and a model are described and then the likelihood is calculated without optimization. To make the script happen, say, to your command line: