                                   fkitsch



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Function

   Fitch-Margoliash method with contemporary tips

Description

   Estimates phylogenies from distance matrix data under the "ultrametric"
   model which is the same as the additive tree model except that an
   evolutionary clock is assumed. The Fitch-Margoliash criterion and other
   least squares criteria, or the Minimum Evolution criterion are
   possible. This program will be useful with distances computed from
   molecular sequences, restriction sites or fragments distances, with
   distances from DNA hybridization measurements, and with genetic
   distances computed from gene frequencies.

Algorithm

   This program carries out the Fitch-Margoliash and Least Squares
   methods, plus a variety of others of the same family, with the
   assumption that all tip species are contemporaneous, and that there is
   an evolutionary clock (in effect, a molecular clock). This means that
   branches of the tree cannot be of arbitrary length, but are constrained
   so that the total length from the root of the tree to any species is
   the same. The quantity minimized is the same weighted sum of squares
   described in the Distance Matrix Methods documentation file.

   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.

   The method may be considered as providing an estimate of the phylogeny.
   Alternatively, it can be considered as a phenetic clustering of the tip
   species. This method minimizes an objective function, the sum of
   squares, not only setting the levels of the clusters so as to do so,
   but rearranging the hierarchy of clusters to try to find alternative
   clusterings that give a lower overall sum of squares. When the power
   option P is set to a value of P = 0.0, so that we are minimizing a
   simple sum of squares of the differences between the observed distance
   matrix and the expected one, the method is very close in spirit to
   Unweighted Pair Group Arithmetic Average Clustering (UPGMA), also
   called Average-Linkage Clustering. If the topology of the tree is fixed
   and there turn out to be no branches of negative length, its result
   should be the same as UPGMA in that case. But since it tries
   alternative topologies and (unless the N option is set) it combines
   nodes that otherwise could result in a reversal of levels, it is
   possible for it to give a different, and better, result than simple
   sequential clustering. Of course UPGMA itself is available as an option
   in program NEIGHBOR.

   An important use of this method will be to do a formal statistical test
   of the evolutionary clock hypothesis. This can be done by comparing the
   sums of squares achieved by FITCH and by KITSCH, BUT SOME CAVEATS ARE
   NECESSARY. First, the assumption is that the observed distances are
   truly independent, that no original data item contributes to more than
   one of them (not counting the two reciprocal distances from i to j and
   from j to i). THIS WILL NOT HOLD IF THE DISTANCES ARE OBTAINED FROM
   GENE FREQUENCIES, FROM MORPHOLOGICAL CHARACTERS, OR FROM MOLECULAR
   SEQUENCES. It may be invalid even for immunological distances and
   levels of DNA hybridization, provided that the use of common standard
   for all members of a row or column allows an error in the measurement
   of the standard to affect all these distances simultaneously. It will
   also be invalid if the numbers have been collected in experimental
   groups, each measured by taking differences from a common standard
   which itself is measured with error. Only if the numbers in different
   cells are measured from independent standards can we depend on the
   statistical model. The details of the test and the assumptions are
   discussed in my review paper on distance methods (Felsenstein, 1984a).
   For further and sometimes irrelevant controversy on these matters see
   the papers by Farris (1981, 1985, 1986) and myself (Felsenstein, 1986,
   1988b).

   A second caveat is that the distances must be expected to rise linearly
   with time, not according to any other curve. Thus it may be necessary
   to transform the distances to achieve an expected linearity. If the
   distances have an upper limit beyond which they could not go, this is a
   signal that linearity may not hold. It is also VERY important to choose
   the power P at a value that results in the standard deviation of the
   variation of the observed from the expected distances being the P/2-th
   power of the expected distance.

   To carry out the test, fit the same data with both FITCH and KITSCH,
   and record the two sums of squares. If the topology has turned out the
   same, we have N = n(n-1)/2 distances which have been fit with 2n-3
   parameters in FITCH, and with n-1 parameters in KITSCH. Then the
   difference between S(K) and S(F) has d1 = n-2 degrees of freedom. It is
   statistically independent of the value of S(F), which has d2 = N-(2n-3)
   degrees of freedom. The ratio of mean squares

      [S(K)-S(F)]/d1
     ----------------
          S(F)/d2


   should, under the evolutionary clock, have an F distribution with n-2
   and N-(2n-3) degrees of freedom respectively. The test desired is that
   the F ratio is in the upper tail (say the upper 5%) of its
   distribution. If the S (subreplication) option is in effect, the above
   degrees of freedom must be modified by noting that N is not n(n-1)/2
   but is the sum of the numbers of replicates of all cells in the
   distance matrix read in, which may be either square or triangular. A
   further explanation of the statistical test of the clock is given in a
   paper of mine (Felsenstein, 1986).

   The program uses a similar tree construction method to the other
   programs in the package and, like them, is not guaranteed to give the
   best-fitting tree. The assignment of the branch lengths for a given
   topology is a least squares fit, subject to the constraints against
   negative branch lengths, and should not be able to be improved upon.
   KITSCH runs more quickly than FITCH.

Usage

   Here is a sample session with fkitsch


% fkitsch
Fitch-Margoliash method with contemporary tips
Phylip distance matrix file: kitsch.dat
Phylip tree file (optional):
Phylip kitsch program output file [kitsch.fkitsch]:

Adding species:
   1. Bovine
   2. Mouse
   3. Gibbon
   4. Orang
   5. Gorilla
   6. Chimp
   7. Human

Doing global rearrangements
  !-------------!
   .............

Output written to file "kitsch.fkitsch"

Tree also written onto file "kitsch.treefile"

Done.



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

Command line arguments

Fitch-Margoliash method with contemporary tips
Version: EMBOSS:6.2.0

   Standard (Mandatory) qualifiers:
  [-datafile]          distances  File containing one or more distance
                                  matrices
  [-intreefile]        tree       Phylip tree file (optional)
  [-outfile]           outfile    [*.fkitsch] Phylip kitsch 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))
   -minev              boolean    [N] Minimum evolution
*  -njumble            integer    [0] Number of times to randomise (Integer 0
                                  or more)
*  -seed               integer    [1] Random number seed between 1 and 32767
                                  (must be odd) (Integer from 1 to 32767)
   -power              float      [2.0] Power (Any numeric value)
   -negallowed         boolean    [N] Negative branch lengths allowed
   -replicates         boolean    [N] Subreplicates
   -[no]trout          toggle     [Y] Write out trees to tree file
*  -outtreefile        outfile    [*.fkitsch] 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
   -odirectory3        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

   fkitsch requires a bifurcating tree, unlike FITCH, which requires an
   unrooted tree with a trifurcation at its base. Thus the tree shown
   below would be written:

     ((D,E),(C,(A,B)));

   If a tree with a trifurcation at the base is by mistake fed into the U
   option of KITSCH then some of its species (the entire rightmost furc,
   in fact) will be ignored and too small a tree read in. This should
   result in an error message and the program should stop. It is important
   to understand the difference between the User Tree formats for KITSCH
   and FITCH. You may want to use RETREE to convert a user tree that is
   suitable for FITCH into one suitable for KITSCH or vice versa.

  Input files for usage example

  File: kitsch.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

   fkitsch output is a rooted tree, together with the sum of squares, the
   number of tree topologies searched, and, if the power P is at its
   default value of 2.0, the Average Percent Standard Deviation is also
   supplied. The lengths of the branches of the tree are given in a table,
   that also shows for each branch the time at the upper end of the
   branch. "Time" here really means cumulative branch length from the
   root, going upwards (on the printed diagram, rightwards). For each
   branch, the "time" given is for the node at the right (upper) end of
   the branch. It is important to realize that the branch lengths are not
   exactly proportional to the lengths drawn on the printed tree diagram!
   In particular, short branches are exaggerated in the length on that
   diagram so that they are more visible.

  Output files for usage example

  File: kitsch.fkitsch


   7 Populations

Fitch-Margoliash method with contemporary tips, version 3.69

                  __ __             2
                  \  \   (Obs - Exp)
Sum of squares =  /_ /_  ------------
                                2
                   i  j      Obs

negative branch lengths not allowed


                                           +-------Human
                                         +-6
                                    +----5 +-------Chimp
                                    !    !
                                +---4    +---------Gorilla
                                !   !
       +------------------------3   +--------------Orang
       !                        !
  +----2                        +------------------Gibbon
  !    !
--1    +-------------------------------------------Mouse
  !
  +------------------------------------------------Bovine


Sum of squares =      0.107

Average percent standard deviation =   5.16213

From     To            Length          Height
----     --            ------          ------

   6   Human           0.13460         0.81285
   5      6            0.02836         0.67825
   6   Chimp           0.13460         0.81285
   4      5            0.07638         0.64990
   5   Gorilla         0.16296         0.81285
   3      4            0.06639         0.57352
   4   Orang           0.23933         0.81285
   2      3            0.42923         0.50713
   3   Gibbon          0.30572         0.81285
   1      2            0.07790         0.07790
   2   Mouse           0.73495         0.81285
   1   Bovine          0.81285         0.81285


  File: kitsch.treefile

((((((Human:0.13460,Chimp:0.13460):0.02836,Gorilla:0.16296):0.07638,
Orang:0.23933):0.06639,Gibbon:0.30572):0.42923,Mouse:0.73495):0.07790,
Bovine:0.81285);

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
                    fneighbor    Phylogenies from distance matrix by N-J or UPGMA method

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.
