
                                 fseqboot 



Function

   Bootstrapped sequences algorithm

Description

   Reads in a data set, and produces multiple data sets from it by
   bootstrap resampling. Since most programs in the current version of
   the package allow processing of multiple data sets, this can be used
   together with the consensus tree program CONSENSE to do bootstrap (or
   delete-half-jackknife) analyses with most of the methods in this
   package. This program also allows the Archie/Faith technique of
   permutation of species within characters. It can also rewrite a data
   set to convert it from between the PHYLIP Interleaved and Sequential
   forms, and into a preliminary version of a new XML sequence alignment
   format which is under development

Algorithm

   SEQBOOT is a general bootstrapping and data set translation tool. It
   is intended to allow you to generate multiple data sets that are
   resampled versions of the input data set. Since almost all programs in
   the package can analyze these multiple data sets, this allows almost
   anything in this package to be bootstrapped, jackknifed, or permuted.
   SEQBOOT can handle molecular sequences, binary characters, restriction
   sites, or gene frequencies. It can also convert data sets between
   Sequential and Interleaved format, and into the NEXUS format or into a
   new XML sequence alignment format.

   To carry out a bootstrap (or jackknife, or permutation test) with some
   method in the package, you may need to use three programs. First, you
   need to run SEQBOOT to take the original data set and produce a large
   number of bootstrapped or jackknifed data sets (somewhere between 100
   and 1000 is usually adequate). Then you need to find the phylogeny
   estimate for each of these, using the particular method of interest.
   For example, if you were using DNAPARS you would first run SEQBOOT and
   make a file with 100 bootstrapped data sets. Then you would give this
   file the proper name to have it be the input file for DNAPARS. Running
   DNAPARS with the M (Multiple Data Sets) menu choice and informing it
   to expect 100 data sets, you would generate a big output file as well
   as a treefile with the trees from the 100 data sets. This treefile
   could be renamed so that it would serve as the input for CONSENSE.
   When CONSENSE is run the majority rule consensus tree will result,
   showing the outcome of the analysis.

   This may sound tedious, but the run of CONSENSE is fast, and that of
   SEQBOOT is fairly fast, so that it will not actually take any longer
   than a run of a single bootstrap program with the same original data
   and the same number of replicates. This is not very hard and allows
   bootstrapping or jackknifing on many of the methods in this package.
   The same steps are necessary with all of them. Doing things this way
   some of the intermediate files (the tree file from the DNAPARS run,
   for example) can be used to summarize the results of the bootstrap in
   other ways than the majority rule consensus method does.

   If you are using the Distance Matrix programs, you will have to add
   one extra step to this, calculating distance matrices from each of the
   replicate data sets, using DNADIST or GENDIST. So (for example) you
   would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
   input, then run (say) NEIGHBOR using the output of DNADIST as its
   input, and then run CONSENSE using the tree file from NEIGHBOR as its
   input.

   The resampling methods available are:
     * The bootstrap. Bootstrapping was invented by Bradley Efron in
       1979, and its use in phylogeny estimation was introduced by me
       (Felsenstein, 1985b; see also Penny and Hendy, 1985). It involves
       creating a new data set by sampling N characters randomly with
       replacement, so that the resulting data set has the same size as
       the original, but some characters have been left out and others
       are duplicated. The random variation of the results from analyzing
       these bootstrapped data sets can be shown statistically to be
       typical of the variation that you would get from collecting new
       data sets. The method assumes that the characters evolve
       independently, an assumption that may not be realistic for many
       kinds of data.
     * The partial bootstrap.. This is the bootstrap where fewer than the
       full number of characters are sampled. The user is asked for the
       fraction of characters to be sampled. It is primarily useful in
       carrying out Zharkikh and Li's (1995) Complete And Partial
       Bootstrap method, and Shimodaira's (2002) AU method, both of which
       correct the bias of bootstrap P values.
     * Block-bootstrapping. One pattern of departure from indeopendence
       of character evolution is correlation of evolution in adjacent
       characters. When this is thought to have occurred, we can correct
       for it by samopling, not individual characters, but blocks of
       adjacent characters. This is called a block bootstrap and was
       introduced by Künsch (1989). If the correlations are believed to
       extend over some number of characters, you choose a block size, B,
       that is larger than this, and choose N/B blocks of size B. In its
       implementation here the block bootstrap "wraps around" at the end
       of the characters (so that if a block starts in the last B-1
       characters, it continues by wrapping around to the first character
       after it reaches the last character). Note also that if you have a
       DNA sequence data set of an exon of a coding region, you can
       ensure that equal numbers of first, second, and third coding
       positions are sampled by using the block bootstrap with B = 3.
     * Partial block-bootstrapping. Similar to partial bootstrapping
       except sampling blocks rather than single characters.
     * Delete-half-jackknifing.. This alternative to the bootstrap
       involves sampling a random half of the characters, and including
       them in the data but dropping the others. The resulting data sets
       are half the size of the original, and no characters are
       duplicated. The random variation from doing this should be very
       similar to that obtained from the bootstrap. The method is
       advocated by Wu (1986). It was mentioned by me in my bootstrapping
       paper (Felsenstein, 1985b), and has been available for many years
       in this program as an option. Note that, for the present,
       block-jackknifing is not available, because I cannot figure out
       how to do it straightforwardly when the block size is not a
       divisor of the number of characters.
     * Delete-fraction jackknifing. Jackknifing is advocated by Farris
       et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
       retains too many characters and will lead to overconfidence in the
       resulting groups when there are conflicting characters. However it
       is made available here as an option, with the user asked to supply
       the fraction of characters that are to be retained.
     * Permuting species within characters. This method of resampling
       (well, OK, it may not be best to call it resampling) was
       introduced by Archie (1989) and Faith (1990; see also Faith and
       Cranston, 1991). It involves permuting the columns of the data
       matrix separately. This produces data matrices that have the same
       number and kinds of characters but no taxonomic structure. It is
       used for different purposes than the bootstrap, as it tests not
       the variation around an estimated tree but the hypothesis that
       there is no taxonomic structure in the data: if a statistic such
       as number of steps is significantly smaller in the actual data
       than it is in replicates that are permuted, then we can argue that
       there is some taxonomic structure in the data (though perhaps it
       might be just the presence of aa pair of sibling species).
     * Permuting characters. This simply permutes the order of the
       characters, the same reordering being applied to all species. For
       many methods of tree inference this will make no difference to the
       outcome (unless one has rates of evolution correlated among
       adjacent sites). It is included as a possible step in carrying out
       a permutation test of homogeneity of characters (such as the
       Incongruence Length Difference test).
     * Permuting characters separately for each species. This is a method
       introduced by Steel, Lockhart, and Penny (1993) to permute data so
       as to destroy all phylogenetic structure, while keeping the base
       composition of each species the same as before. It shuffles the
       character order separately for each species.
     * Rewriting. This is not a resampling or permutation method: it
       simply rewrites the data set into a different format. That format
       can be the PHYLIP format. For molecular sequences and discrete
       morphological character it can also be the NEXUS format. For
       molecular sequences one other format is available, a new (and
       nonstandard) XML format of our own devising. When the PHYLIP
       format is chosen the data set is coverted between Interleaved and
       Sequential format. If it was read in as Interleaved sequences, it
       will be written out as Sequential format, and vice versa. The
       NEXUS format for molecular sequences is always written as
       interleaved sequences. The XML format is different from (though
       similar to) a number of other XML sequence alignment formats. An
       example will be found below. Here is a table to links to those
       other XML alignment formats:

   Andrew Rambaut's BEAST XML format
   http://evolve.zoo.ox.ac.uk/beast/introXML.html and
   http://evolve.zoo.ox.ac.uk/beast/referenindex.html A format for
   alignments. There is also a format for phylogenies described there.
   MSAML M http://xml.coverpages.org/msaml-desc-dec.html Defined by Paul
   Gordon of University of Calgary. See his big list of molecular biology
   XML projects.
   BSML http://www.bsml.org/resources/default.asp Bioinformatic Sequence
   Markup Language includes a multiple sequence alignment XML format

Usage

   Here is a sample session with fseqboot


% fseqboot -seed 3 
Bootstrapped sequences algorithm
Input (aligned) sequence set: seqboot.dat
Phylip seqboot_seq program output file [seqboot.fseqboot]: 


 bootstrap: true
jackknife: false
 permute: false
 lockhart: false
 ild: false
 justwts: false

completed replicate number   10
completed replicate number   20
completed replicate number   30
completed replicate number   40
completed replicate number   50
completed replicate number   60
completed replicate number   70
completed replicate number   80
completed replicate number   90
completed replicate number  100

Output written to file "seqboot.fseqboot"

Done.


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

Command line arguments

   Standard (Mandatory) qualifiers:
  [-sequence]          seqset     (Aligned) sequence set filename and optional
                                  format, or reference (input USA)
  [-outfile]           outfile    [*.fseqboot] Phylip seqboot_seq program
                                  output file

   Additional (Optional) qualifiers (* if not always prompted):
   -categories         properties File of input categories
   -weights            properties Weights file
   -test               menu       [b] Choose test (Values: b (Bootstrap); j
                                  (Jackknife); c (Permute species for each
                                  character); o (Permute character order); s
                                  (Permute within species); r (Rewrite data))
*  -regular            toggle     [N] Altered sampling fraction
*  -fracsample         float      [100.0] Samples as percentage of sites
                                  (Number from 0.100 to 100.000)
*  -rewriteformat      menu       [p] Output format (Values: p (PHYLIP); n
                                  (NEXUS); x (XML))
*  -seqtype            menu       [d] Output format (Values: d (dna); p
                                  (protein); r (rna))
*  -blocksize          integer    [1] Block size for bootstraping (Integer 1
                                  or more)
*  -reps               integer    [100] How many replicates (Integer 1 or
                                  more)
*  -justweights        menu       [d] Write out datasets or just weights
                                  (Values: d (Datasets); w (Weights))
*  -seed               integer    [1] Random number seed between 1 and 32767
                                  (must be odd) (Integer from 1 to 32767)
   -printdata          boolean    [N] Print out the data at start of run
*  -[no]dotdiff        boolean    [Y] Use dot-differencing
   -[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

   fseqboot data files read by SEQBOOT are the standard ones for the
   various kinds of data. For molecular sequences the sequences may be
   either interleaved or sequential, and similarly for restriction sites.
   Restriction sites data may either have or not have the third argument,
   the number of restriction enzymes used. Discrete morphological
   characters are always assumed to be in sequential format. Gene
   frequencies data start with the number of species and the number of
   loci, and then follow that by a line with the number of alleles at
   each locus. The data for each locus may either have one entry for each
   allele, or omit one allele at each locus. The details of the formats
   are given in the main documentation file, and in the documentation
   files for the groups of programsreads any normal sequence USAs.

  Input files for usage example

  File: seqboot.dat

    5    6
Alpha     AACAAC
Beta      AACCCC
Gamma     ACCAAC
Delta     CCACCA
Epsilon   CCAAAC

Output file format

   fseqboot output will contain the data sets generated by the resampling
   process. Note that, when Gene Frequencies data is used or when
   Discrete Morphological characters with the Factors option are used,
   the number of characters in each data set may vary. It may also vary
   if there are an odd number of characters or sites and the
   Delete-Half-Jackknife resampling method is used, for then there will
   be a 50% chance of choosing (n+1)/2 characters and a 50% chance of
   choosing (n-1)/2 characters.

   The Factors option causes the characters to be resampled together. If
   (say) three adjacent characters all have the same factors characters,
   so that they all are understood to be recoding one multistate
   character, they will be resampled together as a group.

   The order of species in the data sets in the output file will vary
   randomly. This is a precaution to help the programs that analyze these
   data avoid any result which is sensitive to the input order of species
   from showing up repeatedly and thus appearing to have evidence in its
   favor.

   The numerical options 1 and 2 in the menu also affect the output file.
   If 1 is chosen (it is off by default) the program will print the
   original input data set on the output file before the resampled data
   sets. I cannot actually see why anyone would want to do this. Option 2
   toggles the feature (on by default) that prints out up to 20 times
   during the resampling process a notification that the program has
   completed a certain number of data sets. Thus if 100 resampled data
   sets are being produced, every 5 data sets a line is printed saying
   which data set has just been completed. This option should be turned
   off if the program is running in background and silence is desirable.
   At the end of execution the program will always (whatever the setting
   of option 2) print a couple of lines saying that output has been
   written to the output file.

  Output files for usage example

  File: seqboot.fseqboot

    5     6
Alpha     AAACCA
Beta      AAACCC
Gamma     ACCCCA
Delta     CCCAAC
Epsilon   CCCAAA
    5     6
Alpha     AAACAA
Beta      AAACCC
Gamma     ACCCAA
Delta     CCCACC
Epsilon   CCCAAA
    5     6
Alpha     AAAAAC
Beta      AAACCC
Gamma     AACAAC
Delta     CCCCCA
Epsilon   CCCAAC
    5     6
Alpha     CCCCCA
Beta      CCCCCC
Gamma     CCCCCA
Delta     AAAAAC
Epsilon   AAAAAA
    5     6
Alpha     AAAACC
Beta      AAACCC
Gamma     AACACC
Delta     CCCCAA
Epsilon   CCCACC
    5     6
Alpha     AAAACC
Beta      ACCCCC
Gamma     AAAACC
Delta     CCCCAA
Epsilon   CAAACC
    5     6
Alpha     AACCAA
Beta      AACCCC
Gamma     ACCCAA
Delta     CCAACC
Epsilon   CCAAAA
    5     6
Alpha     AAAACC
Beta      ACCCCC
Gamma     AAAACC
Delta     CCCCAA
Epsilon   CAAACC
    5     6
Alpha     AACACC


  [Part of this file has been deleted for brevity]

Gamma     ACAAAA
Delta     CCCCCC
Epsilon   CCAAAA
    5     6
Alpha     AACAAC
Beta      AACCCC
Gamma     AACAAC
Delta     CCACCA
Epsilon   CCAAAC
    5     6
Alpha     AACAAA
Beta      AACCCC
Gamma     CCCAAA
Delta     CCACCC
Epsilon   CCAAAA
    5     6
Alpha     ACAAAA
Beta      ACCCCC
Gamma     CCAAAA
Delta     CACCCC
Epsilon   CAAAAA
    5     6
Alpha     CAAAAA
Beta      CCCCCC
Gamma     CAAAAA
Delta     ACCCCC
Epsilon   AAAAAA
    5     6
Alpha     CAACCC
Beta      CCCCCC
Gamma     CAACCC
Delta     ACCAAA
Epsilon   AAACCC
    5     6
Alpha     ACAACC
Beta      ACCCCC
Gamma     ACAACC
Delta     CACCAA
Epsilon   CAAACC
    5     6
Alpha     AAAAAA
Beta      AAAAAC
Gamma     ACCCCA
Delta     CCCCCC
Epsilon   CCCCCA
    5     6
Alpha     AACAAC
Beta      AACCCC
Gamma     CCCAAC
Delta     CCACCA
Epsilon   CCAAAC

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
   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
   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
   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.

Comments

   None
