hmmsim: collect profile HMM score distributions on random sequences
# hmmsim :: collect profile HMM score distributions on random sequences
# HMMER 3.0 (March 2010); http://hmmer.org/
# Copyright (C) 2010 Howard Hughes Medical Institute.
# Freely distributed under the GNU General Public License (GPLv3).
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Usage: hmmsim [-options] <hmmfile>
where general options are:
-h : show brief help on version and usage
-a : obtain alignment length statistics too
-v : verbose: print scores
-L <n> : length of random target seqs [100] (n>0)
-N <n> : number of random target seqs [1000] (n>0)
output options (only in serial mode, for single HMM input):
-o <f> : direct output to file <f>, not stdout
--afile <f> : output alignment lengths to file <f>
--efile <f> : output E vs. E plots to <f> in xy format
--ffile <f> : output filter fraction: # seqs passing P thresh
--pfile <f> : output P(S>x) plots to <f> in xy format
--xfile <f> : output bitscores as binary double vector to <f>
alternative alignment styles :
--fs : multihit local alignment [default]
--sw : unihit local alignment
--ls : multihit glocal alignment
--s : unihit glocal alignment
alternative scoring algorithms :
--vit : score seqs with the Viterbi algorithm [default]
--fwd : score seqs with the Forward algorithm
--hyb : score seqs with the Hybrid algorithm
--msv : score seqs with the MSV algorithm
--fast : use the optimized versions of the above
controlling range of fitted tail masses :
--tmin <x> : set lower bound tail mass for fwd,island [0.02]
--tmax <x> : set lower bound tail mass for fwd,island [0.02]
--tpoints <n> : set number of tail probs to try [1]
--tlinear : use linear not log spacing of tail probs
controlling E-value calibration :
--EmL <n> : length of sequences for MSV Gumbel mu fit [200] (n>0)
--EmN <n> : number of sequences for MSV Gumbel mu fit [200] (n>0)
--EvL <n> : length of sequences for Viterbi Gumbel mu fit [200] (n>0)
--EvN <n> : number of sequences for Viterbi Gumbel mu fit [200] (n>0)
--EfL <n> : length of sequences for Forward exp tail tau fit [100] (n>0)
--EfN <n> : number of sequences for Forward exp tail tau fit [200] (n>0)
--Eft <x> : tail mass for Forward exponential tail tau fit [0.04] (0<x<1)
debugging :
--stall : arrest after start: for debugging MPI under gdb
--seed <n> : set random number seed to <n> [0]
experiments :
--bgflat : set uniform background frequencies
--bgcomp : set bg frequencies to model's average composition
--x-no-lengthmodel : turn the H3 length model off
--nu <x> : set nu parameter (# expected HSPs) for GMSV [2.0]
--pthresh <x> : set P-value threshold for --ffile [0.02]
obtain alignment length statistics too
verbose: print scores
multihit local alignment
unihit local alignment
multihit glocal alignment
unihit glocal alignment
score seqs with the Viterbi algorithm
score seqs with the Forward algorithm
score seqs with the Hybrid algorithm
score seqs with the MSV algorithm
use the optimized versions of the above
use linear not log spacing of tail probs
set uniform background frequencies
set bg frequencies to model's average composition
turn the H3 length model off
length of random target seqs (n>0)
number of random target seqs (n>0)
Direct output to a file, not stdout
output alignment lengths to file
output E vs. E plots to given file in xy format
output filter fraction: # seqs passing P thresh
output P(S>x) plots to given file in xy format
output bitscores as binary double vector to given file
set lower bound tail mass for fwd,island
set lower bound tail mass for fwd,island
set number of tail probs to try
length of sequences for MSV Gumbel mu fit (n>0)
number of sequences for MSV Gumbel mu fit (n>0)
length of sequences for Viterbi Gumbel mu fit (n>0)
number of sequences for Viterbi Gumbel mu fit (n>0)
length of sequences for Forward exp tail tau fit (n>0)
number of sequences for Forward exp tail tau fit (n>0)
tail mass for Forward exponential tail tau fit (0<x<1)
set RNG seed to given value (if 0: one-time arbitrary seed)
set nu parameter (# expected HSPs) for GMSV [default=2.0]
set P-value threshold for --ffile [default=0.02]
The query profile
Returns metadata about the application. This includes usage information, along with any number of arbitrary application-specific metadata specified as an array of info elements, e.g. description of the various options that are passed to the application binary.
Requires all the parameters with correct type, and structures representing the input files. The structure contains the name of the input file and either the contents in Base64 encoded binary form or a MIME attachment, or simply a location (URL) to the associated file. The operation returns a Job ID that can be used to retrieve job status and outputs.
Same as launchJob but blocks until the remote execution is complete, and returns job outputs (as described above) as the response. This operation may only be appropriate for jobs that are not long running.
Expects a Job ID to query the status of a running job. A status code, message, and URL of the working directory for the job are returned.
Returns basic job statistics including start time, activation time and completion time for a given Job ID.
returns the outputs from a job that is identified by a Job ID. The output consists of the urls for the standard output and error, and an array of structures representing the output files. The structure contains the name of the output file and the url from where it can be downloaded.
Returns the contents of an output file as Base64 binary. The input is a data structure that contains the Job ID for a particular job, and the name of the file to be retrieved.
Destroys a running job identified by a Job ID.