Provided by: andi_0.12-4_amd64 bug


       andi - estimates evolutionary distance


       andi [OPTIONS...] FILES...


       andi  estimates  the  evolutionary distance between closely related genomes. For this andi
       reads the input sequences from FASTA files and computes the pairwise anchor distance.  The
       idea behind this is explained in a paper by Haubold et al. (2015).


       The output is a symmetrical distance matrix in 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). For technical reasons the comparison might fail and no estimate can  be
       computed.  In  such  cases nan is printed. This either means that the input sequences were
       too short (<200bp) or too diverse (K>0.5) for our method to work properly.


       -b INT, --bootstrap=INT
              Compute multiple distance matrices, with n-1 bootstrapped from the first.  See  the
              paper Klötzl & Haubold (2016) for a detailed explanation.

              Usually,  andi  is  called  with  the filenames as commandline arguments. With this
              option the filenames may also be read from a file itself, with one name  per  line.
              Use a single dash ('-') to read from stdin.

       -j, --join
              Use  this  mode  if  each of your FASTA files represents one assembly with numerous
              contigs. andi will then treat all of the contained sequences per file as  a  single
              genome.  In  this  mode  at  least  one  filename must be provided via command line
              arguments. For the output the filename is used to identify each sequence.

       -l, --low-memory
              In multithreaded mode, andi requires memory linear to the amount  of  threads.  The
              low  memory mode changes this to a constant demand independent from the used number
              of threads. Unfortunately, this comes at a significant runtime cost.

       -m MODEL, --model=MODEL
              Set the nucleotide evolution model to one of 'Raw', 'JC', or 'Kimura'.  By  default
              the Jukes-Cantor correction is used.

       -p FLOAT
              Significance of an anchor; default: 0.025.

              Print  a  progress  bar.  WHEN  can  be  'auto'  (default if omitted), 'always', or

       -t INT, --threads=INT
              The number of threads to be used; by default, all available processors are used.
              Multithreading is only available if andi was compiled with OpenMP support.

              By default andi outputs the full names of sequences, optionally padded with spaces,
              if  they are shorter than ten characters. Names longer than ten characters may lead
              to problems with downstream tools. With this switch names will be truncated.

       -v, --verbose
              Prints additional information,  including  the  amount  of  found  homology.  Apply
              multiple times for extra verboseness.

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

              Outputs version information and acknowledgments.


       Copyright © 2014 - 2017 Fabian Klötzl 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


       1)  andi:  Haubold,  B.  Klötzl,  F.  and Pfaffelhuber, P. (2015). andi: Fast and accurate
       estimation of evolutionary distances between closely related genomes
       2) Algorithms: Ohlebusch, E. (2013). Bioinformatics Algorithms. Sequence Analysis,  Genome
       Rearrangements, and Phylogenetic Reconstruction. pp 118f.
       3)  SA  construction:  Mori,  Y.  (2005).  Short  description of improved two-stage suffix
       sorting algorithm.
       4) Bootstrapping: Klötzl, F. and Haubold, B. (2016). Support Values for Genome Phylogenies


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