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phmmer(1) HMMER Manual phmmer(1)

phmmer - search protein sequence(s) against a protein sequence database

phmmer [options] seqfile seqdb

phmmer is used to search one or more query protein sequences against a protein sequence database. For each query sequence in seqfile, use that sequence to search the target database of sequences in seqdb, and output ranked lists of the sequences with the most significant matches to the query.

Either the query seqfile or the target seqdb may be '-' (a dash character), in which case the query sequences 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. An exception is that if the seqfile contains more than one query sequence, then seqdb cannot come from <stdin>, because we can't rewind the streaming target database to search it with another query.

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.

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

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

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

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

Save a simple tabular (space-delimited) file summarizing the per-domain output, with one data line per homologous domain detected in a query sequence for each homologous model.

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 volume.

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.

Set the main output's line length limit to <n> characters per line. The default is 120.

The probability model in phmmer is constructed by inferring residue probabilities from a standard 20x20 substitution score matrix, plus two additional parameters for position-independent gap open and gap extend probabilities.

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.

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.

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.

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.)

Reporting thresholds control which hits are reported in output files (the main output, --tblout, and --domtblout). 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.

In the per-target output, 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.

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

In the per-domain output, for target sequences that have already satisfied the per-profile reporting threshold, report individual domains with a conditional E-value of <= <x>. The default is 10.0. A conditional E-value means the expected number of additional false positive domains in the smaller search space of those comparisons that already satisfied the per-target reporting threshold (and thus must have at least one homologous domain already).

Instead of thresholding per-domain output on E-value, instead report domains with a bit score of >= <x>.

Inclusion thresholds are stricter than reporting thresholds. They control which hits are included in any output multiple alignment (the -A option) and which domains are marked as significant ("!") as opposed to questionable ("?") in domain output.

Use an E-value of <= <x> as the per-target 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.

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

Use a conditional E-value of <= <x> as the per-domain inclusion threshold, in targets that have already satisfied the overall per-target inclusion threshold. The default is 0.01.

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

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.

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.

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.

Second filter threshold; set the P-value threshold for the Viterbi filter step. The default is 0.001.

Third filter threshold; 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 load.

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.

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

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

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

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

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

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

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

Turn off the null2 score corrections for biased composition.

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.

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 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.

Assert that input 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. phmmer always uses a single sequence query to start its search, so when the input seqfile is an alignment, phmmer 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 target sequence database seqdb is in format <s>, bypassing format autodetection. See --qformat above for list of accepted format codes for <s>.

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.

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.)

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 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 (C) 2020 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/).

http://eddylab.org

Nov 2020 HMMER 3.3.2