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hmmemit - sample sequences from a profile HMM
hmmemit [options] hmmfile
The hmmemit program samples (emits) sequences from the profile HMM(s) in hmmfile, and
writes them to output. Sampling sequences may be useful for a variety of purposes,
including creating synthetic true positives for benchmarks or tests.
The default is to sample one unaligned sequence from the core probability model, which
means that each sequence consists of one full-length domain. Alternatively, with the -c
option, you can emit a simple majority-rule consensus sequence; or with the -a option, you
can emit an alignment (in which case, you probably also want to set -N to something other
than its default of 1 sequence per model).
As another option, with the -p option you can sample a sequence from a fully configured
HMMER search profile. This means sampling a `homologous sequence' by HMMER's definition,
including nonhomologous flanking sequences, local alignments, and multiple domains per
sequence, depending on the length model and alignment mode chosen for the profile.
The hmmfile may contain a library of HMMs, in which case each HMM will be used in turn.
<hmmfile> may be '-' (dash), which means reading this input from stdin rather than a file.
-h Help; print a brief reminder of command line usage and all available options.
-o <f> Direct the output sequences to file <f>, rather than to stdout.
-N <n> Sample <n> sequences per model, rather than just one.
OPTIONS CONTROLLING WHAT TO EMIT
The default is to sample N sequences from the core model. Alternatively, you may choose
one (and only one) of the following alternatives.
-a Emit an alignment for each HMM in the hmmfile rather than sampling unaligned
sequences one at a time.
-c Emit a plurality-rule consensus sequence, instead of sampling a sequence from the
profile HMM's probability distribution. The consensus sequence is formed by
selecting the maximum probability residue at each match state.
-C Emit a fancier plurality-rule consensus sequence than the -c option. If the maximum
probability residue has p < minl show it as a lower case 'any' residue (n or x); if
p >= minl and < minu show it as a lower case residue; and if p >= minu show it as
an upper case residue. The default settings of minu and minl are both 0.0, which
means -C gives the same output as -c unless you also set minu and minl to what you
-p Sample unaligned sequences from the implicit search profile, not from the core
model. The core model consists only of the homologous states (between the begin
and end states of a HMMER Plan7 model). The profile includes the nonhomologous N,
C, and J states, local/glocal and uni/multihit algorithm configuration, and the
target length model. Therefore sequences sampled from a profile may include
nonhomologous as well as homologous sequences, and may contain more than one
homologous sequence segment. By default, the profile is in multihit local mode, and
the target sequence length is configured for L=400.
OPTIONS CONTROLLING EMISSION FROM PROFILES
These options require that you have set the -p option.
-L <n> Configure the profile's target sequence length model to generate a mean length of
approximately <n> rather than the default of 400.
Configure the profile for multihit local alignment.
Configure the profile for unihit local alignment (Smith/Waterman).
Configure the profile for multihit glocal alignment.
Configure the profile for unihit glocal alignment.
OPTIONS CONTROLLING FANCY CONSENSUS EMISSION
These options require that you have set the -C option.
Sets the minl threshold for showing weakly conserved residues as lower case. (0 <=
x <= 1)
Sets the minu threshold for showing strongly conserved residues as upper case. (0
<= x <= 1)
Seed the random number generator with <n>, an integer >= 0. If <n> is nonzero, 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
is 0: use an arbitrary seed, so different hmmemit runs will generate different
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