Provided by: hmmer_3.1b2+dfsg-5ubuntu1_amd64 bug


       nhmmer - search DNA/RNA queries against a DNA/RNA sequence database


       nhmmer [options] <queryfile> <seqdb>


       nhmmer  is  used  to  search  one or more nucleotide queries against a nucleotide sequence
       database.  For each query in <queryfile>, use that query to search the target database  of
       sequences  in  <seqdb>,  and  output  a  ranked list of the hits with the most significant
       matches to the query. A query may be either  a  profile  model  built  using  hmmbuild,  a
       sequence  alignment,  or  a  single sequence. Sequence based queries can be in a number of
       formats (see --qformat), and can typically  be  autodetected.  Note  that  only  Stockholm
       format supports queries made up of more than one sequence alignment.

       Either the query <queryfile> or the target <seqdb> may be '-' (a dash character), in which
       case the query file or target database input will be read from a <stdin> pipe  instead  of
       from  a  file.  Only one input source can come through <stdin>, not both.  If the query is
       sequence-based and  passed  via  <stdin>,  the  --qformat  flag  must  be  used.   If  the
       <queryfile>  contains  more than one query, then <seqdb> cannot come from <stdin>, because
       we can't rewind the streaming target database to search it with another profile.

       If the query is sequence-based, and not from <stdin>, a new  file  containing  the  HMM(s)
       built  from  the input(s) in <queryfile> may optionally be produced, with the filename set
       using the --hmmout flag.

       The output format is designed to be  human-readable,  but  is  often  so  voluminous  that
       reading it is impractical, and parsing it is a pain. The --tblout option saves output in a
       simple tabular format that  is  concise  and  easier  to  parse.   The  -o  option  allows
       redirecting the main output, including throwing it away in /dev/null.


       -h     Help; print a brief reminder of command line usage and all available options.


       -o <f> Direct the main human-readable output to a file <f> instead of the default stdout.

       -A <f> Save  a  multiple  alignment  of  all  significant hits (those satisfying inclusion
              thresholds) to the file <f>.

       --tblout <f>
              Save a simple tabular (space-delimited) file  summarizing  the  per-target  output,
              with one data line per homologous target sequence found.

       --dfamtblout <f>
              Save  a  tabular  (space-delimited) file summarizing the per-hit output, similar to
              --tblout but more succinct.

       --aliscoresout <f>
              Save to file a list of per-position scores for  each  hit.   This  is  useful,  for
              example,  in  identifying  regions  of  high  score  density  for  use in resolving
              overlapping hits from different models.

       --hmmout <f>
              If <queryfile> is sequence-based, write the internally-computed HMM(s) to <f>.

       --acc  Use accessions instead of names in the main output, where  available  for  profiles
              and/or sequences.

              Omit the alignment section from the main output. This can greatly reduce the output

              Unlimit the length of each line in the main output. The default is a limit  of  120
              characters  per line, which helps in displaying the output cleanly on terminals and
              in editors, but can truncate target profile description lines.

       --textw <n>
              Set the main output's line length limit to <n> characters per line. The default  is


       Reporting  thresholds  control  which  hits are reported in output files (the main output,
       --tblout, and --dfamtblout).  Hits are ranked by statistical significance (E-value).

       -E <x> Report target sequences with an E-value of <= <x>.  The default  is  10.0,  meaning
              that  on  average,  about 10 false positives will be reported per query, so you can
              see the top of the noise and decide for yourself if it's really noise.

       -T <x> Instead of thresholding output on E-value, instead report target sequences  with  a
              bit score of >= <x>.


       Inclusion thresholds are stricter than reporting thresholds.  Inclusion thresholds control
       which hits are considered to be reliable enough to be included in an output alignment or a
       subsequent  search  round, or marked as significant ("!") as opposed to questionable ("?")
       in hit output.

       --incE <x>
              Use an E-value of <= <x> as the inclusion threshold.  The default is 0.01,  meaning
              that  on  average,  about  1 false positive would be expected in every 100 searches
              with different query sequences.

       --incT <x>
              Instead of using E-values for setting the inclusion threshold, use a bit  score  of
              >= <x> as the inclusion threshold.  By default this option is unset.


       Curated  profile  databases  may  define  specific  bit score thresholds for each profile,
       superseding any thresholding based on statistical significance alone.

       To use these options, the profile  must  contain  the  appropriate  (GA,  TC,  and/or  NC)
       optional  score  threshold annotation; this is picked up by hmmbuild from Stockholm format
       alignment files. For a nucleotide model, each thresholding option  has  a  single  per-hit
       threshold  <x>  This  acts  as if -T<x> --incT<x> has been applied specifically using each
       model's curated thresholds.

              Use the GA (gathering) bit score threshold in the model to  set  per-hit  reporting
              and inclusion thresholds. GA thresholds are generally considered to be the reliable
              curated  thresholds  defining  family  membership;  for  example,  in  Dfam,  these
              thresholds  are  applied when annotating a genome with a model of a family known to
              be found in that organism. They may allow  for  minimal  expected  false  discovery

              Use the NC (noise cutoff) bit score threshold in the model to set per-hit reporting
              and inclusion thresholds. NC thresholds are less stringent than GA; in the  context
              of  Pfam,  they  are generally used to store the score of the highest-scoring known
              false positive.

              Use the NC (trusted cutoff) bit  score  threshold  in  the  model  to  set  per-hit
              reporting  and  inclusion thresholds. TC thresholds are more stringent than GA, and
              are generally considered to be the score of the lowest-scoring known true  positive
              that is above all known false positives; for example, in Dfam, these thresholds are
              applied when annotating a genome with a model of a family not known to be found  in
              that organism.


       HMMER3  searches are accelerated in a three-step filter pipeline: the scanning-SSV filter,
       the Viterbi filter, and the Forward filter. The first  filter  is  the  fastest  and  most
       approximate;  the  last is the full Forward scoring algorithm. There is also a bias filter
       step between SSV and Viterbi. Targets that pass all the steps in the acceleration pipeline
       are  then  subjected  to  postprocessing  --  domain  identification and scoring using the
       Forward/Backward algorithm.

       Changing filter thresholds only removes or includes targets from  consideration;  changing
       filter  thresholds  does  not  alter bit scores, E-values, or alignments, all of which are
       determined solely in postprocessing.

       --max  Turn  off  (nearly)  all  filters,  including  the  bias  filter,  and   run   full
              Forward/Backward  postprocessing  on  most  of the target sequence.  In contrast to
              phmmer and hmmsearch, where this flag really does turn off  the  filters  entirely,
              the  --max  flag  in nhmmer sets the scanning-SSV filter threshold to 0.4, not 1.0.
              Use of this flag increases sensitivity somewhat, at a large cost in speed.

       --F1 <x>
              Set the P-value threshold for the SSV filter step.  The default  is  0.02,  meaning
              that  roughly  2% of the highest scoring nonhomologous targets are expected to pass
              the filter.

       --F2 <x>
              Set the P-value threshold for the Viterbi filter step.  The default is 0.001.

       --F3 <x>
              Set the P-value threshold for the Forward filter step.  The default is 1e-5.

              Turn off the bias filter. This increases sensitivity somewhat, but can  come  at  a
              high cost in speed, especially if the query has biased residue composition (such as
              a repetitive sequence region, or if it is a membrane protein with large regions  of
              hydrophobicity).  Without  the  bias filter, too many sequences may pass the filter
              with  biased  queries,  leading  to  slower  than  expected  performance   as   the
              computationally  intensive Forward/Backward algorithms shoulder an abnormally heavy


       The alphabet type of the target database (DNA or  RNA)  is  autodetected  by  default,  by
       looking  at the composition of the <seqdb>.  Autodetection is normally quite reliable, but
       occasionally alphabet type may be ambiguous and autodetection can fail (for instance, when
       the  first  sequence  starts  with  a  run  of ambiguous characters). To avoid this, or to
       increase robustness in automated analysis pipelines, you may specify the alphabet type  of
       <seqdb> with these options.

       --dna  Specify that all sequences in <seqdb> are DNAs.

       --rna  Specify that all sequences in <seqdb> are RNAs.


       When  searching  with nhmmer, one may optionally precompute a binary version of the target
       database, using makehmmerdb, then search against that database.  Using  default  settings,
       this  yields  a roughly 10-fold acceleration with small loss of sensitivity on benchmarks.
       This is achieved using a heuristic method that searches for  seeds  (ungapped  alignments)
       around  which full processing is done. This is essentially a replacement to the SSV stage.
       (This method has been  extensively  tested,  but  should  still  be  treated  as  somewhat
       experimental.)   The  following  options  only  impact nhmmer if the value of --tformat is

       Changing parameters for this seed-finding step will impact both speed  and  sensitivity  -
       typically faster search leads to lower sensitivity.

       --seed_max_depth <n>
              The  seed step requires that a seed reach a specified bit score in length no longer
              than <n>.  By default, this value is 15. Longer seeds allow  a  greater  chance  of
              meeting   the  bit  score  threshold,  leading  to  diminished  filtering  (greater
              sensitivity, slower run time).

       --seed_sc_thresh <x>
              The seed must reach score <x> (in  bits).  The  default  is  15.0  bits.  A  higher
              threshold  increases  filtering  stringency,  leading to faster run times and lower

       --seed_sc_density <x>
              Either all prefixes or all suffixes of a seed  must  have  bit  density  (bits  per
              aligned  position)  of at least <x>.  The default is 0.8 bits/position. An increase
              in the density requirement leads to increased filtering stringency, thus faster run
              times and lower sensitivity.

       --seed_drop_max_len <n>
              A seed may not have a run of length <n> in which the score drops by --seed_drop_lim
              or more. Basically, this prunes seeds that go through long  slightly-negative  seed
              extensions.  The  default  is 4.  Increasing the limit causes (slightly) diminished
              filtering efficiency, thus slower run times and higher sensitivity.  (minor  tuning

       --seed_drop_lim <x>
              In  a  seed,  there  may be no run of length --seed_drop_max_len in which the score
              drops by --seed_drop_lim.  The default  is  0.3  bits.  Larger  numbers  mean  less
              filtering.  (minor tuning option)

       --seed_req_pos <n>
              A  seed must contain a run of at least <n> positive-scoring matches. The default is
              5. Larger values mean increased filtering.  (minor tuning option)

       --seed_ssv_length <n>
              After finding a short seed, an ungapped alignment is extended in both directions in
              an attempt to meet the --F1 score threshold. The window through which this ungapped
              alignment extends is length  <n>.   The  default  is  70.   Decreasing  this  value
              slightly  reduces  run  time, at a small risk of reduced sensitivity. (minor tuning


       --tformat <s>
              Assert that the target sequence database file is in format <s>.   Accepted  formats
              include  fasta,  embl,  genbank,  ddbj,  uniprot,  stockholm,  pfam,  a2m, afa, and
              hmmerfm.  The default is to autodetect the format of the file. The  format  hmmerfm
              indicates  that the database file is a binary file produced using makehmmerdb (this
              format is not currently autodetected).

       --qformat <s>
              Declare that the input <queryfile> is in format <s>.  This is used when  the  query
              is sequence-based, rather than made up of profile model(s).  Currently the accepted
              multiple alignment sequence file formats include Stockholm, Aligned FASTA, Clustal,
              NCBI  PSI-BLAST,  PHYLIP,  Selex,  and  UCSC  SAM A2M. Default is to autodetect the
              format of the file.

              Turn off the null2 score corrections for biased composition.

       -Z <x> For the purposes of per-hit E-value calculations, Assert that the total size of the
              target  database  is  <x>  million  nucleotides,  rather  than the actual number of
              targets seen.

       --seed <n>
              Set the random number seed to <n>.  Some  steps  in  postprocessing  require  Monte
              Carlo  simulation.   The  default  is to use a fixed seed (42), so that results are
              exactly reproducible. Any other positive integer  will  give  different  (but  also
              reproducible) results. A choice of 0 uses a randomly chosen seed.

       --w_beta <x>
              Window length tail mass.  The upper bound, W, on the length at which nhmmer expects
              to find an instance of the model is set such that the  fraction  of  all  sequences
              generated  by  the  model  with length >= W is less than <x>.  The default is 1e-7.
              This flag may be used to override the value of  W  established  for  the  model  by
              hmmbuild, or when the query is sequence-based.

       --w_length <n>
              Override the model instance length upper bound, W, which is otherwise controlled by
              --w_beta.  It should be larger than the model length. The value of W is  used  deep
              in the acceleration pipeline, and modest changes are not expected to impact results
              (though larger values of W do lead to longer run time).  This flag may be  used  to
              override the value of W established for the model by hmmbuild, or when the query is

              Only search the top strand. By default both the query  sequence  and  its  reverse-
              complement are searched.

              Only  search  the  bottom  (reverse-complement)  strand.  By default both the query
              sequence and its reverse-complement are searched.

       --cpu <n>
              Set the number of parallel worker threads to <n>.  By default, HMMER sets  this  to
              the  number of CPU cores it detects in your machine - that is, it tries to maximize
              the use of your available processor cores. Setting <n> higher than  the  number  of
              available  cores is of little if any value, but you may want to set it to something
              less. You can  also  control  this  number  by  setting  an  environment  variable,

              This  option  is  only  available if HMMER was compiled with POSIX threads support.
              This is the default, but it may have been turned off at compile-time for your  site
              or machine for some reason.

              For  debugging  the  MPI  master/worker  version:  pause after start, to enable the
              developer to attach debuggers to the running master and worker(s)  processes.  Send
              SIGCONT  signal  to  release  the  pause.   (Under gdb: (gdb) signal SIGCONT) (Only
              available if optional MPI support was enabled at compile-time.)

       --mpi  Run in MPI master/worker mode, using  mpirun.   (Only  available  if  optional  MPI
              support was enabled at compile-time.)


       See  hmmer(1)  for  a  master  man  page  with  a list of all the individual man pages for
       programs in the HMMER package.

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


       Copyright (C) 2015 Howard Hughes Medical Institute.
       Freely distributed under the GNU General Public License (GPLv3).

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


       Eddy/Rivas Laboratory
       Janelia Farm Research Campus
       19700 Helix Drive
       Ashburn VA 20147 USA