NAME

       alf - Alignment free sequence comparison

       SYNOPSIS

              alf [OPTIONS] -i IN.FASTA [-o OUT.TXT]

       DESCRIPTION

              Compute  pairwise  similarity of sequences using alignment-free methods in IN.FASTA
              and write out tab-delimited matrix with pairwise scores to OUT.TXT.

       -h, --help

              Displays this help message.

       --version

              Display version information

       -v, --verbose

              When given, details about the progress are printed to the screen.

              Input / Output:

       -i, --input-file FILE

              Name of the multi-FASTA input file. Valid filetypes are: fa and fasta.

       -o, --output-file FILE

              Name of the file to which the tab-delimtied matrix with  pairwise  scores  will  be
              written to. Default is to write to stdout. Valid filetype is: alf.tsv.

              General Algorithm Parameters:

       -m, --method METHOD

              Select method to use. One of N2, D2, D2Star, and D2z. Default: N2.

       -k, --k-mer-size K

              Size of the k-mers. Default: 4.

       -mo, --bg-model-order ORDER

              Order of background Markov Model. Default: 1.

              N2 Algorithm Parameters:

       -rc, --reverse-complement MODE

              Which  strand  to score. Use both_strands to score both strands simultaneously. One
              of input, both_strands, mean, min, and max.  Default: input.

       -mm, --mismatches MISMATCHES

              Number of mismatches, one of 0 and 1. When 1 is used, N2 uses  the  k-mer-neighbour
              with one mismatch. Default: 0.

       -mmw, --mismatch-weight WEIGHT

              Real-valued weight of counts for words with mismatches. Default: 0.1.

       -kwf, --k-mer-weights-file FILE.TXT

              Print  k-mer  weights  for every sequence to this file if given. Valid filetype is:
              txt.

       CONTACT AND REFERENCES

              For questions or comments, contact:

              Jonathan Goeke <goeke@molgen.mpg.de>

              Please reference the following publication if you used ALF or  the  N2  method  for
              your analysis:

              Jonathan Goeke, Marcel H. Schulz, Julia Lasserre, and Martin Vingron. Estimation of
              Pairwise Sequence Similarity of Mammalian Enhancers with Word Neighbourhood Counts.
              Bioinformatics (2012).

              Project Homepage:

              http://www.seqan.de/projects/alf

       VERSION

              alf version: 1.1 Last update January 5, 2012