Provided by: seqan-apps_2.4.0+dfsg-15ubuntu1_amd64
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.
OPTIONS
-h, --help Display the help message. --version Display version information. -v, --verbose When given, details about the progress are printed to the screen. Input / Output: -i, --input-file INPUT_FILE Name of the multi-FASTA input file. Valid filetypes are: .sam[.*], .raw[.*], .gbk[.*], .frn[.*], .fq[.*], .fna[.*], .ffn[.*], .fastq[.*], .fasta[.*], .faa[.*], .fa[.*], .embl[.*], and .bam, where * is any of the following extensions: gz, bz2, and bgzf for transparent (de)compression. -o, --output-file OUTPUT_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[.*], where * is any of the following extensions: tsv for transparent (de)compression. General Algorithm Parameters: -m, --method STRING Select method to use. One of N2, D2, D2Star, and D2z. Default: N2. -k, --k-mer-size INTEGER Size of the k-mers. Default: 4. -mo, --bg-model-order INTEGER Order of background Markov Model. Default: 1. N2 Algorithm Parameters: -rc, --reverse-complement STRING 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 INTEGER 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 DOUBLE Real-valued weight of counts for words with mismatches. Default: 0.1. -kwf, --k-mer-weights-file OUTPUT_FILE 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