
                                 fdnadist 



Function

   Nucleic acid sequence Distance Matrix program

Description

   Computes four different distances between species from nucleic acid
   sequences. The distances can then be used in the distance matrix
   programs. The distances are the Jukes-Cantor formula, one based on
   Kimura's 2- parameter method, the F84 model used in DNAML, and the
   LogDet distance. The distances can also be corrected for
   gamma-distributed and gamma-plus-invariant-sites-distributed rates of
   change in different sites. Rates of evolution can vary among sites in
   a prespecified way, and also according to a Hidden Markov model. The
   program can also make a table of percentage similarity among
   sequences.

Algorithm

   This program uses nucleotide sequences to compute a distance matrix,
   under four different models of nucleotide substitution. It can also
   compute a table of similarity between the nucleotide sequences. The
   distance for each pair of species estimates the total branch length
   between the two species, and can be used in the distance matrix
   programs FITCH, KITSCH or NEIGHBOR. This is an alternative to use of
   the sequence data itself in the maximum likelihood program DNAML or
   the parsimony program DNAPARS.

   The program reads in nucleotide sequences and writes an output file
   containing the distance matrix, or else a table of similarity between
   sequences. The four models of nucleotide substitution are those of
   Jukes and Cantor (1969), Kimura (1980), the F84 model (Kishino and
   Hasegawa, 1989; Felsenstein and Churchill, 1996), and the model
   underlying the LogDet distance (Barry and Hartigan, 1987; Lake, 1994;
   Steel, 1994; Lockhart et. al., 1994). All except the LogDet distance
   can be made to allow for for unequal rates of substitution at
   different sites, as Jin and Nei (1990) did for the Jukes-Cantor model.
   The program correctly takes into account a variety of sequence
   ambiguities, although in cases where they exist it can be slow.

   Jukes and Cantor's (1969) model assumes that there is independent
   change at all sites, with equal probability. Whether a base changes is
   independent of its identity, and when it changes there is an equal
   probability of ending up with each of the other three bases. Thus the
   transition probability matrix (this is a technical term from
   probability theory and has nothing to do with transitions as opposed
   to transversions) for a short period of time dt is:

              To:    A        G        C        T
                   ---------------------------------
               A  | 1-3a      a         a       a
       From:   G  |  a       1-3a       a       a
               C  |  a        a        1-3a     a
               T  |  a        a         a      1-3a

   where a is u dt, the product of the rate of substitution per unit time
   (u) and the length dt of the time interval. For longer periods of time
   this implies that the probability that two sequences will differ at a
   given site is:

      p = 3/4 ( 1 - e- 4/3 u t)

   and hence that if we observe p, we can compute an estimate of the
   branch length ut by inverting this to get

     ut = - 3/4 loge ( 1 - 4/3 p )

   The Kimura "2-parameter" model is almost as symmetric as this, but
   allows for a difference between transition and transversion rates. Its
   transition probability matrix for a short interval of time is:


              To:     A        G        C        T
                   ---------------------------------
               A  | 1-a-2b     a         b       b
       From:   G  |   a      1-a-2b      b       b
               C  |   b        b       1-a-2b    a
               T  |   b        b         a     1-a-2b

   where a is u dt, the product of the rate of transitions per unit time
   and dt is the length dt of the time interval, and b is v dt, the
   product of half the rate of transversions (i.e., the rate of a
   specific transversion) and the length dt of the time interval.

   The F84 model incorporates different rates of transition and
   transversion, but also allowing for different frequencies of the four
   nucleotides. It is the model which is used in DNAML, the maximum
   likelihood nucelotide sequence phylogenies program in this package.
   You will find the model described in the document for that program.
   The transition probabilities for this model are given by Kishino and
   Hasegawa (1989), and further explained in a paper by me and Gary
   Churchill (1996).

   The LogDet distance allows a fairly general model of substitution. It
   computes the distance from the determinant of the empirically observed
   matrix of joint probabilities of nucleotides in the two species. An
   explanation of it is available in the chapter by Swofford et, al.
   (1996).

   The first three models are closely related. The DNAML model reduces to
   Kimura's two-parameter model if we assume that the equilibrium
   frequencies of the four bases are equal. The Jukes-Cantor model in
   turn is a special case of the Kimura 2-parameter model where a = b.
   Thus each model is a special case of the ones that follow it,
   Jukes-Cantor being a special case of both of the others.

   The Jin and Nei (1990) correction for variation in rate of evolution
   from site to site can be adapted to all of the first three models. It
   assumes that the rate of substitution varies from site to site
   according to a gamma distribution, with a coefficient of variation
   that is specified by the user. The user is asked for it when choosing
   this option in the menu.

   Each distance that is calculated is an estimate, from that particular
   pair of species, of the divergence time between those two species. For
   the Jukes- Cantor model, the estimate is computed using the formula
   for ut given above, as long as the nucleotide symbols in the two
   sequences are all either A, C, G, T, U, N, X, ?, or - (the latter four
   indicate a deletion or an unknown nucleotide. This estimate is a
   maximum likelihood estimate for that model. For the Kimura 2-parameter
   model, with only these nucleotide symbols, formulas special to that
   estimate are also computed. These are also, in effect, computing the
   maximum likelihood estimate for that model. In the Kimura case it
   depends on the observed sequences only through the sequence length and
   the observed number of transition and transversion differences between
   those two sequences. The calculation in that case is a maximum
   likelihood estimate and will differ somewhat from the estimate
   obtained from the formulas in Kimura's original paper. That formula
   was also a maximum likelihood estimate, but with the
   transition/transversion ratio estimated empirically, separately for
   each pair of sequences. In the present case, one overall preset
   transition/transversion ratio is used which makes the computations
   harder but achieves greater consistency between different comparisons.

   For the F84 model, or for any of the models where one or both
   sequences contain at least one of the other ambiguity codons such as
   Y, R, etc., a maximum likelihood calculation is also done using code
   which was originally written for DNAML. Its disadvantage is that it is
   slow. The resulting distance is in effect a maximum likelihood
   estimate of the divergence time (total branch length between) the two
   sequences. However the present program will be much faster than
   versions earlier than 3.5, because I have speeded up the iterations.

   The LogDet model computes the distance from the determinant of the
   matrix of co-occurrence of nucleotides in the two species, according
   to the formula

   D  = - 1/4(loge(|F|) - 1/2loge(fA1fC1fG1fT1fA2fC2fG2fT2))

   Where F is a matrix whose (i,j) element is the fraction of sites at
   which base i occurs in one species and base j occurs in the other. fji
   is the fraction of sites at which species i has base j. The LogDet
   distance cannot cope with ambiguity codes. It must have completely
   defined sequences. One limitation of the LogDet distance is that it
   may be infinite sometimes, if there are too many changes between
   certain pairs of nucleotides. This can be particularly noticeable with
   distances computed from bootstrapped sequences. Note that there is an
   assumption that we are looking at all sites, including those that have
   not changed at all. It is important not to restrict attention to some
   sites based on whether or not they have changed; doing that would bias
   the distances by making them too large, and that in turn would cause
   the distances to misinterpret the meaning of those sites that had
   changed.

   For all of these distance methods, the program allows us to specify
   that "third position" bases have a different rate of substitution than
   first and second positions, that introns have a different rate than
   exons, and so on. The Categories option which does this allows us to
   make up to 9 categories of sites and specify different rates of change
   for them.

   In addition to the four distance calculations, the program can also
   compute a table of similarities between nucleotide sequences. These
   values are the fractions of sites identical between the sequences. The
   diagonal values are 1.0000. No attempt is made to count similarity of
   nonidentical nucleotides, so that no credit is given for having (for
   example) different purines at corresponding sites in the two
   sequences. This option has been requested by many users, who need it
   for descriptive purposes. It is not intended that the table be used
   for inferring the tree.

Usage

   Here is a sample session with fdnadist


% fdnadist 
Nucleic acid sequence Distance Matrix program
Input (aligned) nucleotide sequence set(s): dnadist.dat
Distance methods
         f : F84 distance model
         k : Kimura 2-parameter distance
         j : Jukes-Cantor distance
         l : LogDet distance
         s : Similarity table
Choose the method to use [F84 distance model]: 
Phylip distance matrix output file [dnadist.fdnadist]: 

Distances calculated for species
    Alpha        ....
    Beta         ...
    Gamma        ..
    Delta        .
    Epsilon

Distances written to file "dnadist.fdnadist"

Done.


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

Command line arguments

   Standard (Mandatory) qualifiers:
  [-sequence]          seqsetall  File containing one or more sequence
                                  alignments
   -method             menu       [F84 distance model] Choose the method to
                                  use (Values: f (F84 distance model); k
                                  (Kimura 2-parameter distance); j
                                  (Jukes-Cantor distance); l (LogDet
                                  distance); s (Similarity table))
  [-outfile]           outfile    [*.fdnadist] Phylip distance matrix output
                                  file

   Additional (Optional) qualifiers (* if not always prompted):
*  -gamma              menu       [No distribution parameters used] Gamma
                                  distribution (Values: g (Gamma distributed
                                  rates); i (Gamma+invariant sites); n (No
                                  distribution parameters used))
*  -ncategories        integer    [1] Number of substitution rate categories
                                  (Integer from 1 to 9)
*  -rate               array      [1.0] Category rates
*  -categories         properties File of substitution rate categories
   -weights            properties Weights file
*  -gammacoefficient   float      [1] Coefficient of variation of substitution
                                  rate among sites (Number 0.001 or more)
*  -invarfrac          float      [0.0] Fraction of invariant sites (Number
                                  from 0.000 to 1.000)
*  -ttratio            float      [2.0] Transition/transversion ratio (Number
                                  0.001 or more)
*  -[no]freqsfrom      toggle     [Y] Use empirical base frequencies from
                                  seqeunce input
*  -basefreq           array      [0.25 0.25 0.25 0.25] Base frequencies for A
                                  C G T/U (use blanks to separate)
   -lower              boolean    [N] Lower triangular distance matrix
   -printdata          boolean    [N] Print data at start of run
   -[no]progress       boolean    [Y] Print indications of progress of run

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

   "-sequence" associated qualifiers
   -sbegin1            integer    Start of each sequence to be used
   -send1              integer    End of each sequence to be used
   -sreverse1          boolean    Reverse (if DNA)
   -sask1              boolean    Ask for begin/end/reverse
   -snucleotide1       boolean    Sequence is nucleotide
   -sprotein1          boolean    Sequence is protein
   -slower1            boolean    Make lower case
   -supper1            boolean    Make upper case
   -sformat1           string     Input sequence format
   -sdbname1           string     Database name
   -sid1               string     Entryname
   -ufo1               string     UFO features
   -fformat1           string     Features format
   -fopenfile1         string     Features file name

   "-outfile" associated qualifiers
   -odirectory2        string     Output directory

   General qualifiers:
   -auto               boolean    Turn off prompts
   -stdout             boolean    Write standard output
   -filter             boolean    Read standard input, write 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. 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

Input file format

   fdnadist reads any normal sequence USAs.

  Input files for usage example

  File: dnadist.dat

   5   13
Alpha     AACGTGGCCACAT
Beta      AAGGTCGCCACAC
Gamma     CAGTTCGCCACAA
Delta     GAGATTTCCGCCT
Epsilon   GAGATCTCCGCCC

Output file format

   fdnadist output contains on its first line the number of species. The
   distance matrix is then printed in standard form, with each species
   starting on a new line with the species name, followed by the
   distances to the species in order. These continue onto a new line
   after every nine distances. If the L option is used, the matrix or
   distances is in lower triangular form, so that only the distances to
   the other species that precede each species are printed. Otherwise the
   distance matrix is square with zero distances on the diagonal. In
   general the format of the distance matrix is such that it can serve as
   input to any of the distance matrix programs.

   If the option to print out the data is selected, the output file will
   precede the data by more complete information on the input and the
   menu selections. The output file begins by giving the number of
   species and the number of characters, and the identity of the distance
   measure that is being used.

   If the C (Categories) option is used a table of the relative rates of
   expected substitution at each category of sites is printed, and a
   listing of the categories each site is in.

   There will then follow the equilibrium frequencies of the four bases.
   If the Jukes-Cantor or Kimura distances are used, these will
   necessarily be 0.25 : 0.25 : 0.25 : 0.25. The output then shows the
   transition/transversion ratio that was specified or used by default.
   In the case of the Jukes-Cantor distance this will always be 0.5. The
   transition-transversion parameter (as opposed to the ratio) is also
   printed out: this is used within the program and can be ignored. There
   then follow the data sequences, with the base sequences printed in
   groups of ten bases along the lines of the Genbank and EMBL formats.

   The distances printed out are scaled in terms of expected numbers of
   substitutions, counting both transitions and transversions but not
   replacements of a base by itself, and scaled so that the average rate
   of change, averaged over all sites analyzed, is set to 1.0 if there
   are multiple categories of sites. This means that whether or not there
   are multiple categories of sites, the expected fraction of change for
   very small branches is equal to the branch length. Of course, when a
   branch is twice as long this does not mean that there will be twice as
   much net change expected along it, since some of the changes may occur
   in the same site and overlie or even reverse each other. The branch
   lengths estimates here are in terms of the expected underlying numbers
   of changes. That means that a branch of length 0.26 is 26 times as
   long as one which would show a 1% difference between the nucleotide
   sequences at the beginning and end of the branch. But we would not
   expect the sequences at the beginning and end of the branch to be 26%
   different, as there would be some overlaying of changes.

   One problem that can arise is that two or more of the species can be
   so dissimilar that the distance between them would have to be
   infinite, as the likelihood rises indefinitely as the estimated
   divergence time increases. For example, with the Jukes-Cantor model,
   if the two sequences differ in 75% or more of their positions then the
   estimate of dovergence time would be infinite. Since there is no way
   to represent an infinite distance in the output file, the program
   regards this as an error, issues an error message indicating which
   pair of species are causing the problem, and stops. It might be that,
   had it continued running, it would have also run into the same problem
   with other pairs of species. If the Kimura distance is being used
   there may be no error message; the program may simply give a large
   distance value (it is iterating towards infinity and the value is just
   where the iteration stopped). Likewise some maximum likelihood
   estimates may also become large for the same reason (the sequences
   showing more divergence than is expected even with infinite branch
   length). I hope in the future to add more warning messages that would
   alert the user the this.

   If the similarity table is selected, the table that is produced is not
   in a format that can be used as input to the distance matrix programs.
   it has a heading, and the species names are also put at the tops of
   the columns of the table (or rather, the first 8 characters of each
   species name is there, the other two characters omitted to save
   space). There is not an option to put the table into a format that can
   be read by the distance matrix programs, nor is there one to make it
   into a table of fractions of difference by subtracting the similarity
   values from 1. This is done deliberately to make it more difficult for
   the use to use these values to construct trees. The similarity values
   are not corrected for multiple changes, and their use to construct
   trees (even after converting them to fractions of difference) would be
   wrong, as it would lead to severe conflict between the distant pairs
   of sequences and the close pairs of sequences.

  Output files for usage example

  File: dnadist.fdnadist

    5
Alpha       0.000000  0.303893  0.857546  1.158921  1.542897
Beta        0.303893  0.000000  0.339731  0.913519  0.619666
Gamma       0.857546  0.339731  0.000000  1.631729  1.293707
Delta       1.158921  0.913519  1.631729  0.000000  0.165882
Epsilon     1.542897  0.619666  1.293707  0.165882  0.000000

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
   distmat      Creates a distance matrix from multiple alignments
   ednacomp     DNA compatibility algorithm
   ednadist     Nucleic acid sequence Distance Matrix program
   ednainvar    Nucleic acid sequence Invariants method
   ednaml       Phylogenies from nucleic acid Maximum Likelihood
   ednamlk      Phylogenies from nucleic acid Maximum Likelihood with clock
   ednapars     DNA parsimony algorithm
   ednapenny    Penny algorithm for DNA
   eprotdist    Protein distance algorithm
   eprotpars    Protein parsimony algorithm
   erestml      Restriction site Maximum Likelihood method
   eseqboot     Bootstrapped sequences algorithm
   fdiscboot    Bootstrapped discrete sites algorithm
   fdnacomp     DNA compatibility algorithm
   fdnainvar    Nucleic acid sequence Invariants method
   fdnaml       Estimates nucleotide phylogeny by maximum likelihood
   fdnamlk      Estimates nucleotide phylogeny by maximum likelihood
   fdnamove     Interactive DNA parsimony
   fdnapars     DNA parsimony algorithm
   fdnapenny    Penny algorithm for DNA
   fdolmove     Interactive Dollo or Polymorphism Parsimony
   ffreqboot    Bootstrapped genetic frequencies algorithm
   fproml       Protein phylogeny by maximum likelihood
   fpromlk      Protein phylogeny by maximum likelihood
   fprotdist    Protein distance algorithm
   fprotpars    Protein parsimony algorithm
   frestboot    Bootstrapped restriction sites algorithm
   frestdist    Distance matrix from restriction sites or fragments
   frestml      Restriction site maximum Likelihood method
   fseqboot     Bootstrapped sequences algorithm
   fseqbootall  Bootstrapped sequences algorithm

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.
