xenial (1) jackhmmer.1.gz

Provided by: hmmer_3.1b2-2_amd64 bug

NAME

       jackhmmer - iteratively search sequence(s) against a protein database

SYNOPSIS

       jackhmmer [options] <seqfile> <seqdb>

DESCRIPTION

       jackhmmer  iteratively  searches  each  query  sequence  in  <seqfile>  against the target sequence(s) in
       <seqdb>.  The first iteration is identical to a phmmer  search.   For  the  next  iteration,  a  multiple
       alignment of the query together with all target sequences satisfying inclusion thresholds is assembled, a
       profile is constructed from this alignment (identical to using hmmbuild on the  alignment),  and  profile
       search of the <seqdb> is done (identical to an hmmsearch with the profile).

       The  query  <seqfile>  may  be  '-' (a dash character), in which case the query sequences are read from a
       <stdin> pipe instead of from a file.  The <seqdb> cannot be read from a <stdin> stream, because jackhmmer
       needs to do multiple passes over the database.

       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 and --domtblout options save output in simple tabular
       formats  that  are  concise  and  easier  to  parse.   The  -o option allows redirecting the main output,
       including throwing it away in /dev/null.

OPTIONS

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

       -N <n> Set the maximum number of iterations to <n>.  The default is 5. If N=1, the result  is  equivalent
              to a phmmer search.

OPTIONS CONTROLLING OUTPUT

       By  default, output for each iteration appears on stdout in a somewhat human readable, somewhat parseable
       format. These options allow redirecting that output or  saving  additional  kinds  of  output  to  files,
       including checkpoint files for each iteration.

       -o <f> Direct the human-readable output to a file <f>.

       -A <f> After  the  final iteration, save an annotated multiple alignment of all hits satisfying inclusion
              thresholds (also including the original query) to <f> in Stockholm format.

       --tblout <f>
              After the final iteration, save a tabular summary of  top  sequence  hits  to  <f>  in  a  readily
              parseable, columnar, whitespace-delimited format.

       --domtblout <f>
              After  the  final  iteration,  save  a  tabular  summary  of  top  domain hits to <f> in a readily
              parseable, columnar, whitespace-delimited format.

       --chkhmm <prefix>
              At  the  start  of  each  iteration,  checkpoint  the  query  HMM,  saving  it  to  a  file  named
              <prefix>-<n>.hmm where <n> is the iteration number (from 1..N).

       --chkali <prefix>
              At  the  end  of  each  iteration,  checkpoint  an  alignment  of all domains satisfying inclusion
              thresholds (e.g. what will become the query HMM for the next iteration), saving it to a file named
              <checkpoint  file  prefix>-<n>.sto  in  Stockholm  format, where <n> is the iteration number (from
              1..N).

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

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

       --notextw
              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 120.

OPTIONS CONTROLLING SINGLE SEQUENCE SCORING (FIRST ITERATION)

       By default, the first iteration uses a search model constructed from a single query sequence. This  model
       is  constructed  using a standard 20x20 substitution matrix for residue probabilities, and two additional
       parameters for position-independent gap open and  gap  extend  probabilities.  These  options  allow  the
       default single-sequence scoring parameters to be changed.

       --popen <x>
              Set  the gap open probability for a single sequence query model to <x>.  The default is 0.02.  <x>
              must be >= 0 and < 0.5.

       --pextend <x>
              Set the gap extend probability for a single sequence query model to <x>.  The default is 0.4.  <x>
              must be >= 0 and < 1.0.

       --mx <s>
              Obtain  residue  alignment probabilities from the built-in substitution matrix named <s>.  Several
              standard matrices are built-in, and do not need to be read from files.  The matrix name <s> can be
              PAM30,  PAM70,  PAM120,  PAM240, BLOSUM45, BLOSUM50, BLOSUM62, BLOSUM80, or BLOSUM90.  Only one of
              the --mx and --mxfile options may be used.

       --mxfile <mxfile>
              Obtain residue alignment probabilities from the substitution matrix in file <mxfile>.  The default
              score  matrix is BLOSUM62 (this matrix is internal to HMMER and does not have to be available as a
              file).  The format of a substitution matrix <mxfile> is the standard  format  accepted  by  BLAST,
              FASTA, and other sequence analysis software.

OPTIONS CONTROLLING REPORTING THRESHOLDS

       Reporting  thresholds  control  which  hits  are reported in output files (the main output, --tblout, and
       --domtblout).  In each iteration, sequence hits and domain hits are ranked  by  statistical  significance
       (E-value)  and output is generated in two sections called per-target and per-domain output. In per-target
       output, by default, all sequence hits with an E-value <= 10 are reported. In the per-domain  output,  for
       each  target that has passed per-target reporting thresholds, all domains satisfying per-domain reporting
       thresholds are reported. By default, these are domains with conditional E-values of <= 10. The  following
       options  allow  you  to  change  the default E-value reporting thresholds, or to use bit score thresholds
       instead.

       -E <x> Report sequences with E-values <= <x> in per-sequence output. The default is 10.0.

       -T <x> Use a bit score threshold for per-sequence output instead of an E-value threshold (any setting  of
              -E is ignored). Report sequences with a bit score of >= <x>.  By default this option is unset.

       -Z <x> Declare  the  total size of the database to be <x> sequences, for purposes of E-value calculation.
              Normally E-values are calculated relative to the size of the database you actually searched  (e.g.
              the  number  of  sequences  in  target_seqdb).   In some cases (for instance, if you've split your
              target sequence database into multiple files for parallelization of your  search),  you  may  know
              better what the actual size of your search space is.

       --domE <x>
              Report  domains  with  conditional  E-values  <= <x> in per-domain output, in addition to the top-
              scoring domain per significant sequence hit. The default is 10.0.

       --domT <x>
              Use a bit score threshold for per-domain output instead of an E-value threshold  (any  setting  of
              --domT is ignored). Report domains with a bit score of >= <x> in per-domain output, in addition to
              the top-scoring domain per significant sequence hit. By default this option is unset.

       --domZ <x>
              Declare the number of significant sequences to be <x> sequences, for purposes  of  conditional  E-
              value   calculation  for  additional  domain  significance.   Normally  conditional  E-values  are
              calculated relative to the number of sequences passing per-sequence reporting threshold.

OPTIONS CONTROLLING INCLUSION THRESHOLDS

       Inclusion thresholds control which hits are included in the multiple alignment  and  profile  constructed
       for  the next search iteration.  By default, a sequence must have a per-sequence E-value of <= 0.001 (see
       -E option) to be included, and any additional domains in it besides  the  top-scoring  one  must  have  a
       conditional  E-value  of  <=  0.001  (see --domE option). The difference between reporting thresholds and
       inclusion thresholds is that inclusion thresholds control which  hits  actually  get  used  in  the  next
       iteration (or the final output multiple alignment if the -A option is used), whereas reporting thresholds
       control what you see in output. Reporting thresholds are generally more loose so you can  see  borderline
       hits in the top of the noise that might be of interest.

       --incE <x>
              Include  sequences  with  E-values <= <x> in subsequent iteration or final alignment output by -A.
              The default is 0.001.

       --incT <x>
              Use a bit score threshold for per-sequence inclusion instead of an E-value threshold (any  setting
              of  --incE  is  ignored). Include sequences with a bit score of >= <x>.  By default this option is
              unset.

       --incdomE <x>
              Include domains with conditional E-values <= <x> in subsequent iteration or final alignment output
              by -A, in addition to the top-scoring domain per significant sequence hit.  The default is 0.001.

       --incdomT <x>
              Use a bit score threshold for per-domain inclusion instead of an E-value threshold (any setting of
              --incT is ignored). Include domains with a bit score of >= <x>.  By default this option is unset.

OPTIONS CONTROLLING ACCELERATION HEURISTICS

       HMMER3 searches are accelerated in a three-step filter pipeline: the MSV 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, slowest but most accurate. There is also a bias filter step between MSV  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.

       Essentially the only free parameters that control HMMER's heuristic filters are  the  P-value  thresholds
       controlling  the  expected fraction of nonhomologous sequences that pass the filters. Setting the default
       thresholds higher will pass a higher proportion of nonhomologous sequence, increasing sensitivity at  the
       expense of speed; conversely, setting lower P-value thresholds will pass a smaller proportion, decreasing
       sensitivity and increasing speed. Setting a filter's P-value threshold to 1.0 means it will  passing  all
       sequences, and effectively disables the filter.

       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  Maximum   sensitivity.    Turn   off  all  filters,  including  the  bias  filter,  and  run  full
              Forward/Backward postprocessing on every target. This increases sensitivity slightly, at  a  large
              cost in speed.

       --F1 <x>
              First  filter  threshold; set the P-value threshold for the MSV 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>
              Second  filter  threshold;  set the P-value threshold for the Viterbi filter step.  The default is
              0.001.

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

       --nobias
              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 load.

OPTIONS CONTROLLING PROFILE CONSTRUCTION (LATER ITERATIONS)

       These options control how consensus columns are defined in multiple alignments when building profiles. By
       default,  jackhmmer  always  includes  your  original  query  sequence  in  the alignment result at every
       iteration, and consensus positions are defined by that query  sequence:  that  is,  a  default  jackhmmer
       profile is always the same length as your original query, at every iteration.

       --fast Define  consensus columns as those that have a fraction >= symfrac of residues as opposed to gaps.
              (See below for the --symfrac option.) Although this is the  default  profile  construction  option
              elsewhere  (in  hmmbuild,  in particular), it may have undesirable effects in jackhmmer, because a
              profile could iteratively walk in sequence space away from your original query, leaving few or  no
              consensus columns corresponding to its residues.

       --hand Define  consensus  columns  in  next profile using reference annotation to the multiple alignment.
              jackhmmer propagates reference annotation from the previous profile to the multiple alignment, and
              thence to the next profile. This is the default.

       --symfrac <x>
              Define the residue fraction threshold necessary to define a consensus column when using the --fast
              option. The default is 0.5. The symbol fraction in each column is calculated after taking relative
              sequence  weighting  into  account,  and ignoring gap characters corresponding to ends of sequence
              fragments (as opposed to internal insertions/deletions).  Setting this to  0.0  means  that  every
              alignment  column  will be assigned as consensus, which may be useful in some cases. Setting it to
              1.0 means that only columns that include 0 gaps (internal insertions/deletions) will  be  assigned
              as consensus.

       --fragthresh <x>
              We  only  want  to  count  terminal gaps as deletions if the aligned sequence is known to be full-
              length, not if it is a fragment (for instance, because only part of it was sequenced). HMMER  uses
              a simple rule to infer fragments: if the sequence length L is less than or equal to a fraction <x>
              times the alignment length in columns, then the sequence is handled as a fragment. The default  is
              0.5.  Setting --fragthresh0 will define no (nonempty) sequence as a fragment; you might want to do
              this if you know you've got a carefully  curated  alignment  of  full-length  sequences.   Setting
              --fragthresh1  will  define all sequences as fragments; you might want to do this if you know your
              alignment is entirely composed of fragments, such as translated short reads in metagenomic shotgun
              data.

OPTIONS CONTROLLING RELATIVE WEIGHTS

       Whenever  a profile is built from a multiple alignment, HMMER uses an ad hoc sequence weighting algorithm
       to downweight closely related sequences and upweight distantly related  ones.  This  has  the  effect  of
       making  models  less  biased  by uneven phylogenetic representation. For example, two identical sequences
       would typically each receive half the weight that one sequence would (and this  is  why  jackhmmer  isn't
       concerned  about  always including your original query sequence in each iteration's alignment, even if it
       finds it again in the database you're searching). These options control which algorithm gets used.

       --wpb  Use the Henikoff position-based sequence weighting scheme [Henikoff and Henikoff,  J.  Mol.  Biol.
              243:574, 1994].  This is the default.

       --wgsc Use  the  Gerstein/Sonnhammer/Chothia weighting algorithm [Gerstein et al, J. Mol. Biol. 235:1067,
              1994].

       --wblosum
              Use the same clustering scheme that was used to weight  data  in  calculating  BLOSUM  subsitution
              matrices  [Henikoff  and  Henikoff,  Proc.  Natl. Acad. Sci 89:10915, 1992]. Sequences are single-
              linkage clustered at an identity threshold (default 0.62; see --wid) and within each cluster of  c
              sequences, each sequence gets relative weight 1/c.

       --wnone
              No relative weights. All sequences are assigned uniform weight.

       --wid <x>
              Sets  the identity threshold used by single-linkage clustering when using --wblosum.  Invalid with
              any other weighting scheme. Default is 0.62.

OPTIONS CONTROLLING EFFECTIVE SEQUENCE NUMBER

       After relative weights are determined, they are normalized to sum to a total effective  sequence  number,
       eff_nseq.   This  number  may be the actual number of sequences in the alignment, but it is almost always
       smaller than that.  The default entropy weighting method (--eent) reduces the effective  sequence  number
       to  reduce  the  information  content  (relative entropy, or average expected score on true homologs) per
       consensus position. The target relative entropy is controlled by a two-parameter function, where the  two
       parameters are settable with --ere and --esigma.

       --eent Adjust  effective sequence number to achieve a specific relative entropy per position (see --ere).
              This is the default.

       --eclust
              Set effective sequence number to the number of single-linkage  clusters  at  a  specific  identity
              threshold  (see  --eid).  This option is not recommended; it's for experiments evaluating how much
              better --eent is.

       --enone
              Turn off effective sequence number determination and just use the actual number of sequences.  One
              reason  you  might  want  to  do  this is to try to maximize the relative entropy/position of your
              model, which may be useful for short models.

       --eset <x>
              Explicitly set the effective sequence number for all models to <x>.

       --ere <x>
              Set the minimum relative entropy/position target to <x>.  Requires --eent.  Default depends on the
              sequence alphabet; for protein sequences, it is 0.59 bits/position.

       --esigma <x>
              Sets the minimum relative entropy contributed by an entire model alignment, over its whole length.
              This has the effect of making short models have higher relative entropy per  position  than  --ere
              alone would give. The default is 45.0 bits.

       --eid <x>
              Sets  the  fractional pairwise identity cutoff used by single linkage clustering with the --eclust
              option. The default is 0.62.

OPTIONS CONTROLLING PRIORS

       In profile construction, by  default,  weighted  counts  are  converted  to  mean  posterior  probability
       parameter  estimates  using  mixture  Dirichlet  priors.   Default mixture Dirichlet prior parameters for
       protein models and for nucleic acid (RNA and DNA) models are built in. The following options allow you to
       override the default priors.

       --pnone  Don't  use  any  priors.  Probability  parameters will simply be the observed frequencies, after
       relative sequence weighting.

       --plaplace Use a Laplace +1 prior in place of the default mixture Dirichlet prior.

OPTIONS CONTROLLING E-VALUE CALIBRATION

       Estimating the location parameters for the expected score distributions for MSV  filter  scores,  Viterbi
       filter scores, and Forward scores requires three short random sequence simulations.

       --EmL <n>
              Sets  the sequence length in simulation that estimates the location parameter mu for MSV filter E-
              values. Default is 200.

       --EmN <n>
              Sets the number of sequences in simulation that estimates the location parameter mu for MSV filter
              E-values. Default is 200.

       --EvL <n>
              Sets the sequence length in simulation that estimates the location parameter mu for Viterbi filter
              E-values. Default is 200.

       --EvN <n>
              Sets the number of sequences in simulation that estimates the location parameter  mu  for  Viterbi
              filter E-values. Default is 200.

       --EfL <n>
              Sets  the  sequence  length in simulation that estimates the location parameter tau for Forward E-
              values. Default is 100.

       --EfN <n>
              Sets the number of sequences in simulation that estimates the location parameter tau  for  Forward
              E-values. Default is 200.

       --Eft <x>
              Sets the tail mass fraction to fit in the simulation that estimates the location parameter tau for
              Forward evalues. Default is 0.04.

OTHER OPTIONS

       --nonull2
              Turn off the null2 score corrections for biased composition.

       -Z <x> Assert that the total number of targets in your searches is <x>, for the purposes of  per-sequence
              E-value calculations, rather than the actual number of targets seen.

       --domZ <x>
              Assert  that  the  total number of targets in your searches is <x>, for the purposes of per-domain
              conditional E-value calculations, rather than the number of  targets  that  passed  the  reporting
              thresholds.

       --seed <n>
              Seed  the  random  number  generator  with  <n>,  an  integer  >= 0.  If <n> is >0, any stochastic
              simulations will be reproducible; the same command will give the same results.  If <n> is  0,  the
              random  number  generator  is seeded arbitrarily, and stochastic simulations will vary from run to
              run of the same command.  The default seed is 42.

       --qformat <s>
              Declare that the input query_seqfile is in format <s>.  Accepted  sequence  file  formats  include
              FASTA,  EMBL, GenBank, DDBJ, UniProt, Stockholm, and SELEX. Default is to autodetect the format of
              the file.

       --tformat <s>
              Declare that the input target_seqdb is in format <s>.   Accepted  sequence  file  formats  include
              FASTA,  EMBL, GenBank, DDBJ, UniProt, Stockholm, and SELEX. Default is to autodetect the format of
              the file.

       --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, HMMER_NCPU.

              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.

       --stall
              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 ALSO

       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 ().

AUTHOR

       Eddy/Rivas Laboratory
       Janelia Farm Research Campus
       19700 Helix Drive
       Ashburn VA 20147 USA
       http://eddylab.org