NAME

       HMMER - profile HMMs for biological sequence analysis

SYNOPSIS

       hmmalign
         Align sequences to a profile

       hmmbuild
         Construct profiles from multiple sequence alignments

       hmmconvert
         Convert profile file to various formats

       hmmemit
         Sample sequences from a profile

       hmmfetch
         Retrieve profiles from a file

       hmmlogo
         Produce a conservation logo graphic from a profile

       hmmpgmd
         Daemon for database search web services

       hmmpress
         Prepare a profile database for hmmscan

       hmmscan
         Search sequence(s) against a profile database

       hmmsearch
         Search profile(s) against a sequence database

       hmmsim
         Collect profile score distributions on random sequences

       hmmstat
         Summary statistics for a profile file

       jackhmmer
         Iteratively search sequence(s) against a sequence database

       makehmmerdb
         build nhmmer database from a sequence file

       nhmmer
         Search DNA/RNA queries against a DNA/RNA sequence database

       nhmmscan
         Search DNA/RNA sequence(s) against a DNA/RNA profile database

       phmmer
         Search protein sequence(s) against a protein sequence database

       alimask
         Calculate and add column mask to a multiple sequence alignment

DESCRIPTION

       HMMER  is  a suite of several programs for biological sequence alignment and database homology search. It
       uses probabilistic models called "profile hidden Markov models" (profile HMMs) to  represent  the  likely
       evolutionary homologs of a single sequence or a multiple alignment of a sequence family. A main avenue of
       research is to improve the evolutionary predictive models in HMMER to be able to recognize and accurately
       align increasingly remote homologs, distant in time.

       HMMER  is  also  used  as an organizational tool, to group the exponentially growing number of biological
       sequences into a vastly smaller set of well-annotated sequence families. New sequences can  be  annotated
       by  comparison  against  curated  sequence  family  databases  of prebuilt HMMER profiles, in addition or
       instead of comparison to the entire sequence database. Databases such as Pfam, SMART, and TIGRfams, among
       others, are based on this principle.

       HMMER  is  used  in  three  main modes: to search a sequence database for new homologs of a sequence or a
       sequence family; to search a profile database (like Pfam) to find what  known  family  a  query  sequence
       belongs  to,  or what domains it has; and to automatically construct large multiple alignments (i.e. with
       an effectively unlimited number of sequences) using a profile representative of a sequence family.

       Suppose you have a multiple sequence alignment of a sequence family of interest, and you want to search a
       sequence  database  for  additional  homologs.  The  hmmbuild  program  builds  profile(s)  from multiple
       alignment(s).  The hmmsearch program searches protein profile(s) against a protein sequence database, and
       nhmmer searches nucleotide profile(s) against a nucleotide sequence database.

       Suppose you have a single sequence of interest, and you want to search a sequence database for additional
       homologs. The phmmer program searches a single protein sequence against a protein sequence database.  The
       jackhmmer  program  does  the  same  thing  but  iteratively -- homologs detected in a previous round are
       incorporated into a new profile, and the new profile is searched again.  phmmer is used like BLASTP,  and
       jackhmmer  is  used  like  a  protein PSI-BLAST. The nhmmer program searches a single nucleotide sequence
       against a nucleotide sequence.

       Suppose you have sequence(s) that you want to analyze using a HMMER-based profile HMM database like  Pfam
       (http://pfam.sanger.ac.uk).   The  hmmpress  program formats a profile HMM flatfile (such as the file you
       would download from Pfam) into a HMMER binary database.  The hmmscan program searches protein sequence(s)
       against  that  database.   The  nhmmscan  program  can  similarly search nucleotide sequence(s) against a
       pressed database of nucleotide profiles, such as from Dfam (http://dfam.janelia.org).

       Suppose you want to align lots of sequences.  You  can  construct  a  manageably  small  alignment  of  a
       representative set of sequences, build a profile with hmmbuild, and use the hmmalign program to align any
       number of sequences to that profile.

       HMMER also includes some auxiliary tools for working with large profile databases.  hmmfetch fetches  one
       or more profiles from a database.  hmmstat prints summary statistics about a profile file.

       For  compatibility  with  other  profile  software and previous versions of HMMER, the hmmconvert program
       converts profiles to a few other formats. We intend to add more support for other formats over time.

       The hmmemit program generates (simulates) "homologous" sequences by sampling from a profile. It can  also
       generate a "consensus" sequence.

       The  hmmsim  program  is  a  simulator used for collecting statistics about score distributions on random
       sequences.

       Each program has its own man page.

SEE ALSO

       This is a summary man page for the entire HMMER3 package.  See individual  man  pages  [hmmbuild(1),  for
       example] for usage, options, and description of each program in the package.

       For complete documentation, see the user guide that came with your HMMER distribution (Userguide.pdf); or
       see the HMMER web page (http://hmmer.org/).

COPYRIGHT

       Copyright (C) 2019 Howard Hughes Medical Institute.
       Freely distributed under the BSD open source license.

       For additional information on copyright and licensing, see the file called COPYRIGHT in your HMMER source
       distribution, or see the HMMER web page (http://hmmer.org/).

AUTHOR

       http://eddylab.org