Provided by: hmmer_3.4+dfsg-2_amd64 
NAME
jackhmmer - iteratively search sequence(s) against a sequence 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 needs to be a 'normal' sequence file. It cannot be read from a stdin stream, because jackhmmer
needs to do multiple passes over the database. It cannot be a compressed (gzipped) file either, because
we treat gzipped files essentially as stdin streams, calling an external decompression program.
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
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. See ftp.ncbi.nlm.nih.gov/blast/matrices/ for example
files. (The only exception: we require matrices to be square, so for DNA, use files like NCBI's
NUC.4.4, not NUC.4.2.)
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
--domE 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
--incdomE 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)
jackhmmer always includes your original query sequence in the alignment result at every iteration, and
consensus positions are always defined by that query sequence. That is, a jackhmmer profile is always the
same length as your original query, at every iteration. Therefore jackhmmer gives you less control over
profile construction than hmmbuild does; it does not have the --fast, or --hand, or --symfrac options.
The only profile construction option available in jackhmmer is --fragthresh:
--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 --fragthresh 0 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
--fragthresh 1 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 substitution
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>
Assert that input query seqfile is in format <s>, bypassing format autodetection. Common choices
for <s> include: fasta, embl, genbank. Alignment formats also work; common choices include:
stockholm, a2m, afa, psiblast, clustal, phylip. jackhmmer always uses a single sequence query to
start its search, so when the input seqfile is an alignment, jackhmmer reads it one unaligned
query sequence at a time, not as an alignment. For more information, and for codes for some less
common formats, see main documentation. The string <s> is case-insensitive (fasta or FASTA both
work).
--tformat <s>
Assert that the input target sequence seqdb is in format <s>. See --qformat above for accepted
choices for <s>.
--cpu <n>
Set the number of parallel worker threads to <n>. On multicore machines, the default is 2. You
can also control this number by setting an environment variable, HMMER_NCPU. There is also a
master thread, so the actual number of threads that HMMER spawns is <n>+1.
This option is not available if HMMER was compiled with POSIX threads support turned off.
--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 under MPI control with master/worker parallelization (using mpirun, for example, or
equivalent). 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 (http://hmmer.org/).
COPYRIGHT
Copyright (C) 2023 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
HMMER 3.4 Aug 2023 jackhmmer(1)