                                  fneighbor



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Function

   Phylogenies from distance matrix by N-J or UPGMA method

Description

   An implementation by Mary Kuhner and John Yamato of Saitou and Nei's
   "Neighbor Joining Method," and of the UPGMA (Average Linkage
   clustering) method. Neighbor Joining is a distance matrix method
   producing an unrooted tree without the assumption of a clock. UPGMA
   does assume a clock. The branch lengths are not optimized by the least
   squares criterion but the methods are very fast and thus can handle
   much larger data sets.

Algorithm

   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 programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
   which comes in the form of a matrix of pairwise distances between all
   pairs of taxa, such as distances based on molecular sequence data, gene
   frequency genetic distances, amounts of DNA hybridization, or
   immunological distances. In analyzing these data, distance matrix
   programs implicitly assume that:
     * Each distance is measured independently from the others: no item of
       data contributes to more than one distance.
     * The distance between each pair of taxa is drawn from a distribution
       with an expectation which is the sum of values (in effect amounts
       of evolution) along the tree from one tip to the other. The
       variance of the distribution is proportional to a power p of the
       expectation.

   These assumptions can be traced in the least squares methods of
   programs FITCH and KITSCH but it is not quite so easy to see them in
   operation in the Neighbor-Joining method of NEIGHBOR, where the
   independence assumptions is less obvious.

   THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
   be expected to be true in most kinds of data, such as genetic distances
   from gene frequency data. For genetic distance data in which pure
   genetic drift without mutation can be assumed to be the mechanism of
   change CONTML may be more appropriate. However, FITCH, KITSCH, and
   NEIGHBOR will not give positively misleading results (they will not
   make a statistically inconsistent estimate) provided that additivity
   holds, which it will if the distance is computed from the original data
   by a method which corrects for reversals and parallelisms in evolution.
   If additivity is not expected to hold, problems are more severe. A
   short discussion of these matters will be found in a review article of
   mine (1984a). For detailed, if sometimes irrelevant, controversy see
   the papers by Farris (1981, 1985, 1986) and myself (1986, 1988b).

   For genetic distances from gene frequencies, FITCH, KITSCH, and
   NEIGHBOR may be appropriate if a neutral mutation model can be assumed
   and Nei's genetic distance is used, or if pure drift can be assumed and
   either Cavalli-Sforza's chord measure or Reynolds, Weir, and
   Cockerham's (1983) genetic distance is used. However, in the latter
   case (pure drift) CONTML should be better.

   Restriction site and restriction fragment data can be treated by
   distance matrix methods if a distance such as that of Nei and Li (1979)
   is used. Distances of this sort can be computed in PHYLIp by the
   program RESTDIST.

   For nucleic acid sequences, the distances computed in DNADIST allow
   correction for multiple hits (in different ways) and should allow one
   to analyse the data under the presumption of additivity. In all of
   these cases independence will not be expected to hold. DNA
   hybridization and immunological distances may be additive and
   independent if transformed properly and if (and only if) the standards
   against which each value is measured are independent. (This is rarely
   exactly true).

   FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
   the branch lengths unconstrained. KITSCH and the UPGMA option of
   NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
   according to which the true branch lengths from the root of the tree to
   each tip are the same: the expected amount of evolution in any lineage
   is proportional to elapsed time.

Usage

   Here is a sample session with fneighbor


% fneighbor
Phylogenies from distance matrix by N-J or UPGMA method
Phylip distance matrix file: neighbor.dat
Phylip neighbor program output file [neighbor.fneighbor]:



Cycle   4: species 1 (   0.91769) joins species 2 (   0.76891)
Cycle   3: node 1 (   0.42027) joins species 3 (   0.35793)
Cycle   2: species 6 (   0.15168) joins species 7 (   0.11752)
Cycle   1: node 1 (   0.04648) joins species 4 (   0.28469)
last cycle:
 node 1  (   0.02696) joins species 5  (   0.15393) joins node 6  (   0.03982)

Output written on file "neighbor.fneighbor"

Tree written on file "neighbor.treefile"

Done.



   Go to the input files for this example
   Go to the output files for this example

Command line arguments

Phylogenies from distance matrix by N-J or UPGMA method
Version: EMBOSS:6.2.0

   Standard (Mandatory) qualifiers:
  [-datafile]          distances  Phylip distance matrix file
  [-outfile]           outfile    [*.fneighbor] Phylip neighbor program output
                                  file

   Additional (Optional) qualifiers (* if not always prompted):
   -matrixtype         menu       [s] Type of data matrix (Values: s (Square);
                                  u (Upper triangular); l (Lower triangular))
   -treetype           menu       [n] Neighbor-joining or UPGMA tree (Values:
                                  n (Neighbor-joining); u (UPGMA))
*  -outgrno            integer    [0] Species number to use as outgroup
                                  (Integer 0 or more)
   -jumble             toggle     [N] Randomise input order of species
*  -seed               integer    [1] Random number seed between 1 and 32767
                                  (must be odd) (Integer from 1 to 32767)
   -replicates         boolean    [N] Subreplicates
   -[no]trout          toggle     [Y] Write out trees to tree file
*  -outtreefile        outfile    [*.fneighbor] Phylip tree output file
                                  (optional)
   -printdata          boolean    [N] Print data at start of run
   -[no]progress       boolean    [Y] Print indications of progress of run
   -[no]treeprint      boolean    [Y] Print out tree

   Advanced (Unprompted) qualifiers: (none)
   Associated qualifiers:

   "-outfile" associated qualifiers
   -odirectory2        string     Output directory

   "-outtreefile" associated qualifiers
   -odirectory         string     Output directory

   General qualifiers:
   -auto               boolean    Turn off prompts
   -stdout             boolean    Write first file to standard output
   -filter             boolean    Read first file from standard input, write
                                  first file to standard output
   -options            boolean    Prompt for standard and additional values
   -debug              boolean    Write debug output to program.dbg
   -verbose            boolean    Report some/full command line options
   -help               boolean    Report command line options and exit. More
                                  information on associated and general
                                  qualifiers can be found with -help -verbose
   -warning            boolean    Report warnings
   -error              boolean    Report errors
   -fatal              boolean    Report fatal errors
   -die                boolean    Report dying program messages
   -version            boolean    Report version number and exit


Input file format

   fneighbor reads any normal sequence USAs.

  Input files for usage example

  File: neighbor.dat

    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 file format

   fneighbor 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.

  Output files for usage example

  File: neighbor.fneighbor


Neighbor-Joining/UPGMA method version 3.69


   7 Populations

 Neighbor-joining method

 Negative branch lengths allowed


  +---------------------------------------------Mouse
  !
  !                        +---------------------Gibbon
  1------------------------2
  !                        !  +----------------Orang
  !                        +--4
  !                           ! +--------Gorilla
  !                           +-5
  !                             ! +--------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             4            0.04648
   4          Orang           0.28469
   4             5            0.02696
   5          Gorilla         0.15393
   5             3            0.03982
   3          Chimp           0.15168
   3          Human           0.11752
   1          Bovine          0.91769



  File: neighbor.treefile

(Mouse:0.76891,(Gibbon:0.35793,(Orang:0.28469,(Gorilla:0.15393,
(Chimp:0.15168,Human:0.11752):0.03982):0.02696):0.04648):0.42027,Bovine:0.91769)
;

Data files

   None

Notes

   None.

References

   None.

Warnings

   None.

Diagnostic Error Messages

   None.

Exit status

   It always exits with status 0.

Known bugs

   None.

See also

                    Program name                       Description
                    efitch       Fitch-Margoliash and Least-Squares Distance Methods
                    ekitsch      Fitch-Margoliash method with contemporary tips
                    eneighbor    Phylogenies from distance matrix by N-J or UPGMA method
                    ffitch       Fitch-Margoliash and Least-Squares Distance Methods
                    fkitsch      Fitch-Margoliash method with contemporary tips

Author(s)

                    This program is an EMBOSS conversion of a program written by Joe
                    Felsenstein as part of his PHYLIP package.

                    Although we take every care to ensure that the results of the EMBOSS
                    version are identical to those from the original package, we recommend
                    that you check your inputs give the same results in both versions
                    before publication.

                    Please report all bugs in the EMBOSS version to the EMBOSS bug team,
                    not to the original author.

History

                    Written (2004) - Joe Felsenstein, University of Washington.

                    Converted (August 2004) to an EMBASSY program by the EMBOSS team.

Target users

                    This program is intended to be used by everyone and everything, from
                    naive users to embedded scripts.
