Three more functions & some more methods in Rphylip

I just added a few more functions to the Rphylip project, my R interface for the PHYLIP package. The new interface functions are Rpars (for PARS), Rmix (for MIX), and Rpenny (for PENNY). All three of these are parsimony method programs: the first does heuristic MP search from unordered, multistate data; whereas the latter do (Wagner, Camin-Sokal, or mixed method) MP searching using heuristic or branch-and-bound algorithms, respectively. More details on the programs can be found by referring to the PHYLIP documentation pages linked above.

I also created a new class of data object, "phylip.data", which just generalizes "proseq" (in Rphylip) and "DNAbin" (in ape), and is very simple.

Here's a quick demo using Rpenny. Note that branch-and-bound should generally not be used for more than a dozen or so taxa (it will become computationally prohibitive quickly).

> require(Rphylip)
Loading required package: Rphylip
Loading required package: ape
> packageVersion("Rphylip")
[1] ‘0.1.14’
> data(primates.bin)
> primates.bin
12 character value sequences stored in a matrix.

All sequences of same length: 231

Labels: Lemur Tarsier Sq.Monkey J.Macaque R.Macaque E.Macaque ...

Trait value composition:
    0     1
0.406 0.594
> tree<-Rpenny(primates.bin)

....

How many
trees looked                                 Approximate
at so far    Length of      How many         percentage
(multiples   shortest tree  trees this long  searched
of  100):    found so far   found so far     so far
----------   ------------   ------------     ------------
     1       -                      0            0.00
     2       -                      0            0.00
     3       -                      0            0.00
     4       208.00000              3            0.00
     5       208.00000              6            0.00
     6       208.00000              6            0.14
     7       208.00000              6            1.90
     8       208.00000              6            6.67
     9       208.00000              6            9.33
    10       208.00000              6           14.00
    11       208.00000              6           37.78
    12       208.00000              6           53.33

Output written to file "outfile"

Trees also written onto file "outtree"

Press enter to quit.

Penny algorithm, version 3.695
 branch-and-bound to find all most parsimonious trees

Wagner parsimony method


                                    requires a total of            208.000

    6 trees in all found


  +--------------------------------1
  ! 
  !  +-----------------------------2        
  !  ! 
--1  !                       +-----10       
  !  !                    +-10 
  !  !                    !  !  +--11       
  !  !                 +--6  +--8 
  !  !                 !  !     +--12       
  +--2     +-----------5  ! 
     !     !           !  +--------9        
     !     !           ! 
     !     !           +-----------8        
     !  +--4 
     !  !  !                 +-----6        
     !  !  !              +-11 
     !  !  !              !  !  +--5        
     +--3  +--------------7  +--9 
        !                 !     +--7        
        !                 ! 
        !                 +--------4        
        ! 
        +--------------------------3        

  remember: this is an unrooted tree!

....

Translation table
-----------------
        1       Lemur
        2       Tarsier
        3       Sq.Monkey
        4       J.Macaque
        5       R.Macaque
        6       E.Macaque
        7       B.Macaque
        8       Gibbon
        9       Orangutan
        10      Gorilla
        11      Chimp
        12      Human

Rooted tree(s) with the outgroup
------------------------
Tarsier, Lemur

> require(phytools)
Loading required package: phytools
Loading required package: maps
Loading required package: rgl
> par(mfrow=c(3,2))
> plotTree(tree)
Waiting to confirm page change...

(These are the six equally most parsimonious trees found by PENNY.)

Cool. The latest version of Rphylip can be downloaded here, and is also on GitHub.