fdnapars

 

Function

DNA parsimony algorithm

Description

Estimates phylogenies by the parsimony method using nucleic acid sequences. Allows use the full IUB ambiguity codes, and estimates ancestral nucleotide states. Gaps treated as a fifth nucleotide state. It can also fo transversion parsimony. Can cope with multifurcations, reconstruct ancestral states, use 0/1 character weights, and infer branch lengths

Algorithm

This program carries out unrooted parsimony (analogous to Wagner trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA sequences. The method of Fitch (1971) is used to count the number of changes of base needed on a given tree. The assumptions of this method are analogous to those of MIX:
  1. Each site evolves independently.
  2. Different lineages evolve independently.
  3. The probability of a base substitution at a given site is small over the lengths of time involved in a branch of the phylogeny.
  4. The expected amounts of change in different branches of the phylogeny do not vary by so much that two changes in a high-rate branch are more probable than one change in a low-rate branch.
  5. The expected amounts of change do not vary enough among sites that two changes in one site are more probable than one change in another.

That these are the assumptions of parsimony methods has been documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b, 1988b). For an opposing view arguing that the parsimony methods make no substantive assumptions such as these, see the papers by Farris (1983) and Sober (1983a, 1983b, 1988), but also read the exchange between Felsenstein and Sober (1986).

Change from an occupied site to a deletion is counted as one change. Reversion from a deletion to an occupied site is allowed and is also counted as one change. Note that this in effect assumes that a deletion N bases long is N separate events.

Dnapars can handle both bifurcating and multifurcating trees. In doing its search for most parsimonious trees, it adds species not only by creating new forks in the middle of existing branches, but it also tries putting them at the end of new branches which are added to existing forks. Thus it searches among both bifurcating and multifurcating trees. If a branch in a tree does not have any characters which might change in that branch in the most parsimonious tree, it does not save that tree. Thus in any tree that results, a branch exists only if some character has a most parsimonious reconstruction that would involve change in that branch. It also saves a number of trees tied for best (you can alter the

number it saves using the V option in the menu). When rearranging trees, it tries rearrangements of all of the saved trees. This makes the algorithm slower than earlier versions of Dnapars.

The input data is standard. The first line of the input file contains the number of species and the number of sites.

Next come the species data. Each sequence starts on a new line, has a ten-character species name that must be blank-filled to be of that length, followed immediately by the species data in the one-letter code. The sequences must either be in the "interleaved" or "sequential" formats described in the Molecular Sequence Programs document. The I option selects between them. The sequences can have internal blanks in the sequence but there must be no extra blanks at the end of the terminated line. Note that a blank is not a valid symbol for a deletion.

Usage

Here is a sample session with fdnapars 


% fdnapars 
DNA parsimony algorithm
Input (aligned) nucleotide sequence set(s): dnapars.dat
Phylip tree file (optional): 
Phylip dnapars program output file [dnapars.fdnapars]: 

Adding species:
   1. Alpha     
   2. Beta      
   3. Gamma     
   4. Delta     
   5. Epsilon   

Doing global rearrangements on the first of the trees tied for best
  !---------!
   .........
   .........

Collapsing best trees
   .

Output written to file "dnapars.fdnapars"

Tree also written onto file "dnapars.treefile"

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
  [-intreefile]        tree       Phylip tree file (optional)
  [-outfile]           outfile    [*.fdnapars] Phylip dnapars program output
                                  file

   Additional (Optional) qualifiers (* if not always prompted):
   -weights            properties Weights file
   -maxtrees           integer    [10000] Number of trees to save (Integer
                                  from 1 to 1000000)
*  -[no]thorough       toggle     [Y] More thorough search
*  -[no]rearrange      boolean    [Y] Rearrange on just one best tree
   -transversion       boolean    [N] Use transversion parsimony
*  -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)
   -outgrno            integer    [0] Species number to use as outgroup
                                  (Integer 0 or more)
   -thresh             toggle     [N] Use threshold parsimony
*  -threshold          float      [1.0] Threshold value (Number 1.000 or more)
   -[no]trout          toggle     [Y] Write out trees to tree file
*  -outtreefile        outfile    [*.fdnapars] Phylip tree output file
                                  (optional)
   -printdata          boolean    [N] Print data at start of run
   -[no]progress       boolean    [Y] Print indications of progress of run
   -stepbox            boolean    [N] Print out steps in each site
   -ancseq             boolean    [N] Print sequences at all nodes of tree
   -[no]treeprint      boolean    [Y] Print out tree
*  -[no]dotdiff        boolean    [Y] Use dot differencing to display results

   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
   -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. 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

Standard (Mandatory) qualifiers Allowed values Default
[-sequence]
(Parameter 1)		 File containing one or more sequence alignments Readable sets of sequences Required
[-intreefile]
(Parameter 2)		 Phylip tree file (optional) Phylogenetic tree  
[-outfile]
(Parameter 3)		 Phylip dnapars program output file Output file <*>.fdnapars
Additional (Optional) qualifiers Allowed values Default
-weights Weights file Property value(s)  
-maxtrees Number of trees to save Integer from 1 to 1000000 10000
-[no]thorough More thorough search Toggle value Yes/No Yes
-[no]rearrange Rearrange on just one best tree Boolean value Yes/No Yes
-transversion Use transversion parsimony Boolean value Yes/No No
-njumble Number of times to randomise Integer 0 or more 0
-seed Random number seed between 1 and 32767 (must be odd) Integer from 1 to 32767 1
-outgrno Species number to use as outgroup Integer 0 or more 0
-thresh Use threshold parsimony Toggle value Yes/No No
-threshold Threshold value Number 1.000 or more 1.0
-[no]trout Write out trees to tree file Toggle value Yes/No Yes
-outtreefile Phylip tree output file (optional) Output file <*>.fdnapars
-printdata Print data at start of run Boolean value Yes/No No
-[no]progress Print indications of progress of run Boolean value Yes/No Yes
-stepbox Print out steps in each site Boolean value Yes/No No
-ancseq Print sequences at all nodes of tree Boolean value Yes/No No
-[no]treeprint Print out tree Boolean value Yes/No Yes
-[no]dotdiff Use dot differencing to display results Boolean value Yes/No Yes
Advanced (Unprompted) qualifiers Allowed values Default
(none)

Input file format

fdnapars reads any normal sequence USAs.

Input files for usage example

File: dnapars.dat

   5   13
Alpha     AACGUGGCCAAAU
Beta      AAGGUCGCCAAAC
Gamma     CAUUUCGUCACAA
Delta     GGUAUUUCGGCCU
Epsilon   GGGAUCUCGGCCC

Output file format

fdnapars output is standard: if option 1 is toggled on, the data is printed out, with the convention that "." means "the same as in the first species". Then comes a list of equally parsimonious trees. Each tree has branch lengths. These are computed using an algorithm published by Hochbaum and Pathria (1997) which I first heard of from Wayne Maddison who invented it independently of them. This algorithm averages the number of reconstructed changes of state over all sites a over all possible most parsimonious placements of the changes of state among branches. Note that it does not correct in any way for multiple changes that overlay each other. If option 2 is toggled on a table of the number of changes of state required in each character is also printed. If option 5 is toggled on, a table is printed out after each tree, showing for each branch whether there are known to be changes in the branch, and what the states are inferred to have been at the top end of the branch. This is a reconstruction of the ancestral sequences in the tree. If you choose option 5, a menu item "." appears which gives you the opportunity to turn off dot-differencing so that complete ancestral sequences are shown. If the inferred state is a "?" or one of the IUB ambiguity symbols, there will be multiple equally-parsimonious assignments of states; the user must work these out for themselves by hand. A "?" in the reconstructed states means that in addition to one or more bases, a deletion may or may not be present. If option 6 is left in its default state the trees found will be written to a tree file, so that they are available to be used in other programs. If the U (User Tree) option is used and more than one tree is supplied, the program also performs a statistical test of each of these trees against the best tree. This test, which is a version of the test proposed by Alan Templeton (1983) and evaluated in a test case by me (1985a). It is closely parallel to a test using log likelihood differences due to Kishino and Hasegawa (1989), and uses the mean and variance of step differences between trees, taken across sites. If the mean is more than 1.96 standard deviations different then the trees are declared significantly different. The program prints out a table of the steps for each tree, the differences of each from the best one, the variance of that quantity as determined by the step differences at individual sites, and a conclusion as to whether that tree is or is not significantly worse than the best one. If the U (User Tree) option is used and more than one tree is supplied, and the program is not told to assume autocorrelation between the rates at different sites, the program also performs a statistical test of each of these trees against the one with highest likelihood. If there are two user trees, this is a version of the test proposed by Alan Templeton (1983) and evaluated in a test case by me (1985a). It is closely parallel to a test using log likelihood differences due to Kishino and Hasegawa (1989) It uses the mean and variance of the differences in the number of steps between trees, taken across sites. If the two trees' means are more than 1.96 standard deviations different, then the trees are declared significantly different. If there are more than two trees, the test done is an extension of the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that a correction for the number of trees was necessary, and they introduced a resampling method to make this correction. In the version used here the variances and covariances of the sums of steps across sites are computed for all pairs of trees. To test whether the difference between each tree and the best one is larger than could have been expected if they all had the same expected number of steps, numbers of steps for all trees are sampled with these covariances and equal means (Shimodaira and Hasegawa's "least favorable hypothesis"), and a P value is computed from the fraction of times the difference between the tree's value and the lowest number of steps exceeds that actually observed. Note that this sampling needs random numbers, and so the program will prompt the user for a random number seed if one has not already been supplied. With the two-tree KHT test no random numbers are used. In either the KHT or the SH test the program prints out a table of the number of steps for each tree, the differences of each from the lowest one, the variance of that quantity as determined by the differences of the numbers of steps at individual sites, and a conclusion as to whether that tree is or is not significantly worse than the best one. Option 6 in the menu controls whether the tree estimated by the program is written onto a tree file. The default name of this output tree file is "outtree". If the U option is in effect, all the user-defined trees are written to the output tree file. If the program finds multiple trees tied for best, all of these are written out onto the output tree file. Each is followed by a numerical weight in square brackets (such as [0.25000]). This is needed when we use the trees to make a consensus tree of the results of bootstrapping or jackknifing, to avoid overrepresenting replicates that find many tied trees.

Output files for usage example

File: dnapars.fdnapars


DNA parsimony algorithm, version 3.67


One most parsimonious tree found:


                                            +-----Epsilon   
               +----------------------------3  
  +------------2                            +-------Delta     
  |            |  
  |            +----------------Gamma     
  |  
  1----Beta      
  |  
  +---------Alpha     


requires a total of     19.000

  between      and       length
  -------      ---       ------
     1           2       0.217949
     2           3       0.487179
     3      Epsilon      0.096154
     3      Delta        0.134615
     2      Gamma        0.275641
     1      Beta         0.076923
     1      Alpha        0.173077

File: dnapars.treefile

(((Epsilon:0.09615,Delta:0.13462):0.48718,Gamma:0.27564):0.21795,
Beta:0.07692,Alpha:0.17308);

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 Create a distance matrix from a multiple sequence alignment
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
fdnadist Nucleic acid sequence Distance Matrix program
fdnainvar Nucleic acid sequence Invariants method
fdnaml Estimates nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
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.