NAME

       hmm_train  -  Estimate  the  transition  probabilities  of  an HMM, based on multiple -g <gff_fname_list>
       [OPTIONS] > out.hmm

DESCRIPTION:

       Estimate the transition probabilities of an HMM, based on multiple alignments, sequence annotations,  and
       a category map.

OPTIONS

   required options
       -m <msa_fname_list>

              List of multiple sequence alignment files.  Currently, in testing mode, the list must be of length
              one.

       -c <category_map_fname>

              File defining mapping of feature types to category numbers.

       -g <gff_fname_list>

              Files in GFF defining sequence features to be used in labeling  sites.    Frame  of  reference  of
              feature indices is determined feature-by-feature according to

       'seqname' attribute.
              Filenames must correspond in number and order

              to the elements of <msa_fname_list>.

   alignment options
       -M <msa_length_list>

              (Mutually exclusive with -m) Assume alignments of the specified lengths (comma-separated list) and
              do not not attempt to map the coordinates in the specified GFFs (assume they are  in  the  desired
              coordinate  frame).   This  option  allows  an  HMM  to  be  trained  directly  from GFFs, without
              alignments.  Not permitted with -I.

       -i PHYLIP|FASTA|MPM|SS

              (default SS) Alignment format.

       -R <tag>

              Before estimating transition probabilities, group features  by  <tag>  (e.g.,  "transcript_id"  or
              "exon_id") and reverse complement segments of the alignment corresponding to groups on the reverse
              strand.  Groups must be non-overlapping (see refeature --unique).

   indel options
       -I <indel_cat_list>

       Model indels for specified categories.
              To have

              nonzero probability for the states corresponding to a specified category  range,  indels  must  be
              "clean"  (nonoverlapping),  must be assignable by parsimony to a single branch in the phylogenetic
              tree, and must have lengths that are exact multiples of the category range size.   Avoid  -G  with
              this option.  If used in training mode, requires -T.

       -t <tree_fname>

              Use the specified tree topology when training for indels.

       -n <nseqs>

              Train  an  indel  model for <nseqs> sequences, despite that the training alignment has a different
              number.  All (non-trivial) gap patterns are assumed to be equally frequent.

   other options
       -q

              Proceed quietly (without updates to stderr).

       -h

              Print this help message and exit.