NAME

       spaced - alignment-free sequence comparison

SYNOPSIS

       spaced [-r] [-k INT] [-l INT] [-n INT] [-t INT] [-d TYPE] [-f FILE] FILES...

DESCRIPTION

       Spaced  Words  is  a  new  approach  to  alignment-free  sequence  comparison.  While most
       alignment-free algorithms compare the word-composition of sequences, Spaced Words  uses  a
       pattern of care and don't care positions. The occurrence of a spaced word in a sequence is
       then defined by the characters at the match positions only, while the  characters  at  the
       don't  care  positions  are  ignored  (this  was  originally inspired by the PatternHunter
       algorithm for homology search in databases).  Instead  of  comparing  the  frequencies  of
       contiguous  words in the input sequences, our new approach compares the frequencies of the
       spaced words according to  the  pre-defined  pattern.  An  information-theoretic  distance
       measure  is  then used to define pairwise distances on the set of input sequences based on
       their spaced-word frequencies. The original  version  of  our  spaced-words  approach  was
       published in Boden et al.(2013).

OUTPUT

       The  output  is  a  symmetrical  distance matrix similar to PHYLIP format, with each entry
       representing divergence with a positive real number. A distance of  zero  means  that  two
       sequences   are   identical,  whereas  other  values  are  estimates  for  the  nucleotide
       substitution rate (Jukes-Cantor corrected).

OPTIONS

       -o <file>
              Print the distance matrix to the given file. Default is DMat.

       -k <int>
              Set the patterns weight. Default: 14.

       -l <int>
              Set don't care positions for the used patterns. Default: 15.

       -n <int>
              Set the number of patterns. Default: 5.

       -f <file>
              Instead of generating new patterns, use read them from the given file.

       -t <INT>
              The number of threads to be used; by default, 25 threads are used.
              Multithreading is only available if spaced was compiled with OpenMP support.

       -r     Skip comparison with the reverse complement.

       -d <type>
              The distances can  be  compute  with  different  measures.  Available  options  are
              Euclidean (EU), Jensen-Shannon (JS), and evolutionary distance (EV). Default: EV.

       -h     Prints the synopsis and an explanation of available options.

COPYRIGHT

       Copyright   ©  2016  Chris  Leimeister  <chris.leimeister@stud.uni-goettingen.de>  License
       GPLv3+: GNU GPL version 3 or later.
       This is free software: you are free to change and redistribute it.  There is NO  WARRANTY,
       to   the   extent   permitted   by   law.    The   full   license  text  is  available  at
       <http://gnu.org/licenses/gpl.html>.

REFERENCES

       1) C.-A. Leimeister, M. Boden,  S.  Horwege,  S.  Lindner,  B.  Morgenstern  (2014).  Fast
       alignment-free   sequence   comparison   using   spaced-word  frequencies,  Bioinformatics
       <http://bioinformatics.oxfordjournals.org/content/early/2014/04/03/bioinformatics.btu177>
       2) S. Horwege, S. Linder, M. Boden, K. Hatje, M. Kollmar, C.-A. Leimeister, B. Morgenstern
       (2014).  Spaced  words and kmacs: fast alignment-free sequence comparison based on inexact
       word        matches,        Nucleic        Acids        Research        42,         W7-W11
       <http://nar.oxfordjournals.org/content/42/W1/W7.abstract>
       3)  B.  Morgenstern,  B.  Zhu, S. Horwege, C.-A Leimeister (2015). Estimating evolutionary
       distances between genomic sequences from spaced-word  matches,  Algorithms  for  Molecular
       Biology 10,5

BUGS

   Reporting Bugs
       Please    report   bugs   to   <kloetzl@evolbio.mpg.de>   or   <chris.leimeister@stud.uni-
       goettingen.de>.