version 3.69

# Neighbor -- Neighbor-Joining and UPGMA methods

© Copyright 1991-2012 by the University of Washington. Written by Joseph Felsenstein. Permission is granted to copy this document provided that no fee is charged for it and that this copyright notice is not removed.

This program implements the Neighbor-Joining method of Saitou and Nei (1987) and the UPGMA method of clustering. The program was written by Mary Kuhner and Jon Yamato, using some code from program Fitch. An important part of the code was translated from FORTRAN code from the neighbor-joining program written by Naruya Saitou and by Li Jin, and is used with the kind permission of Drs. Saitou and Jin.

Neighbor constructs a tree by successive clustering of lineages, setting branch lengths as the lineages join. The tree is not rearranged thereafter. The tree does not assume an evolutionary clock, so that it is in effect an unrooted tree. It should be somewhat similar to the tree obtained by Fitch. The program cannot evaluate a User tree, nor can it prevent branch lengths from becoming negative. However the algorithm is far faster than Fitch or Kitsch. This will make it particularly effective in their place for large studies or for bootstrap or jackknife resampling studies which require runs on multiple data sets.

The UPGMA option constructs a tree by successive (agglomerative) clustering using an average-linkage method of clustering. It has some relationship to Kitsch, in that when the tree topology turns out the same, the branch lengths with UPGMA will turn out to be the same as with the P = 0 option of Kitsch.

The options for Neighbor are selected through the menu, which looks like this:

    Neighbor-Joining/UPGMA method version 3.69

    Settings for this run:
      N       Neighbor-joining or UPGMA tree?  Neighbor-joining
      O                        Outgroup root?  No, use as outgroup species  1
      L         Lower-triangular data matrix?  No
      R         Upper-triangular data matrix?  No
      S                        Subreplicates?  No
      J     Randomize input order of species?  No. Use input order
      M           Analyze multiple data sets?  No
      0   Terminal type (IBM PC, ANSI, none)?  ANSI
      1    Print out the data at start of run  No
      2  Print indications of progress of run  Yes
      3                        Print out tree  Yes
      4       Write out trees onto tree file?  Yes

      Y to accept these or type the letter for one to change

Most of the input options (L, R, S, J, and M) are as given in the Distance Matrix Programs documentation file, and their input format is the same as given there. The O (Outgroup) option is described in the main documentation file of this package. It is not available when the UPGMA option is selected. The Jumble option (J) does not allow multiple jumbles (as most of the other programs that have it do), as there is no objective way of choosing which of the multiple results is best, there being no explicit criterion for optimality of the tree.

An important use of the Jumble option is in the use of Neighbor with bootstrap samples. Backeljau et al. (1996) and Farris et al. (1996) point out that when there are ties in the distance matrix, Neighbor will resolve them in a way dependent on the order of species in the input file. If we have many bootstrap samples from a data set, and run Neighbor on them, we can then get apparent strong support for one resolution of a multifurcation, purely as an artifact of the order of species in the input file. By using a random order of input species for each bootstrap, the problem disappears, as Farris et al. (1996) acknowledge. Neighbor therefore has the Jumble option turned on whenever multiple distance matrices (the M option) is activated. Only one Jumble needs to be done per data set in that case.

Option N chooses between the Neighbor-Joining and UPGMA methods. Option S is the usual Subreplication option. Here, however, it is present only to allow Neighbor to read the input data: the number of replicates is actually ignored, even though it is read in. Note that this means that one cannot use it to have missing data in the input file, if Neighbor is to be used.

The output consists of an tree (rooted if UPGMA, unrooted if Neighbor-Joining) and the lengths of the interior segments. The Average Percent Standard Deviation is not computed or printed out. If the tree found by Neighbor is fed into Fitch as a User Tree, it will compute this quantity if one also selects the N option of Fitch to ensure that none of the branch lengths is re-estimated.

As Neighbor runs it prints out an account of the successive clustering levels, if you allow it to. This is mostly for reassurance and can be suppressed using menu option 2. In this printout of cluster levels the word "OTU" refers to a tip species, and the word "NODE" to an interior node of the resulting tree.

The constants available for modification at the beginning of the program are "namelength" which gives the length of a species name, and the usual boolean constants that initialize the terminal type. There is no feature saving multiple trees tied for best, partly because we do not expect exact ties except in cases where the branch lengths make the nature of the tie obvious, as when a branch is of zero length.

The major advantage of Neighbor is its speed: it requires a time only proportional to the cube of the number of species. It is significantly faster than version 3.5 of this program. By contrast Fitch and Kitsch require a time that rises as the fourth power of the number of species. Thus Neighbor is well-suited to bootstrapping studies and to analysis of very large trees. Our simulation studies (Kuhner and Felsenstein, 1994) show that, contrary to statements in the literature by others, Neighbor does not get as accurate an estimate of the phylogeny as does Fitch. However it does nearly as well, and in view of its speed this will make it a quite useful program.

### TEST DATA SET

        7
    Bovine      0.0000  1.6866  1.7198  1.6606  1.5243  1.6043  1.5905
    Mouse       1.6866  0.0000  1.5232  1.4841  1.4465  1.4389  1.4629
    Gibbon      1.7198  1.5232  0.0000  0.7115  0.5958  0.6179  0.5583
    Orang       1.6606  1.4841  0.7115  0.0000  0.4631  0.5061  0.4710
    Gorilla     1.5243  1.4465  0.5958  0.4631  0.0000  0.3484  0.3083
    Chimp       1.6043  1.4389  0.6179  0.5061  0.3484  0.0000  0.2692
    Human       1.5905  1.4629  0.5583  0.4710  0.3083  0.2692  0.0000

### OUTPUT FROM TEST DATA SET (with all numerical options on)

       7 Populations

    Neighbor-Joining/UPGMA method version 3.69

     Neighbor-joining method

     Negative branch lengths allowed

    Name                       Distances
    ----                       ---------

    Bovine        0.00000   1.68660   1.71980   1.66060   1.52430   1.60430
                  1.59050
    Mouse         1.68660   0.00000   1.52320   1.48410   1.44650   1.43890
                  1.46290
    Gibbon        1.71980   1.52320   0.00000   0.71150   0.59580   0.61790
                  0.55830
    Orang         1.66060   1.48410   0.71150   0.00000   0.46310   0.50610
                  0.47100
    Gorilla       1.52430   1.44650   0.59580   0.46310   0.00000   0.34840
                  0.30830
    Chimp         1.60430   1.43890   0.61790   0.50610   0.34840   0.00000
                  0.26920
    Human         1.59050   1.46290   0.55830   0.47100   0.30830   0.26920
                  0.00000

      +---------------------------------------------Mouse
      !
      !                        +---------------------Gibbon
      1------------------------2
      !                        !  +----------------Orang
      !                        +--5
      !                           ! +--------Gorilla
      !                           +-4
      !                             ! +--------Chimp
      !                             +-3
      !                               +------Human
      !
      +------------------------------------------------------Bovine

    remember: this is an unrooted tree!

    Between        And            Length
    -------        ---            ------
       1          Mouse           0.76891
       1             2            0.42027
       2          Gibbon          0.35793
       2             5            0.04648
       5          Orang           0.28469
       5             4            0.02696
       4          Gorilla         0.15393
       4             3            0.03982
       3          Chimp           0.15167
       3          Human           0.11753
       1          Bovine          0.91769