NAME

SYNOPSIS

DESCRIPTION

hmms is designed to be useful for detecting complete proteins (or, less commonly, complete nucleic acid sequences) in sequence databases. The requirement for a complete match to the model means that it is useful only for whole-sequence models; for instance, a globin HMM will recognize other complete globin sequences (though it will not recognize the few proteins with multiple globin domains!)

Another use for hmms is to score the sequences of a training database, during the construction of a new HMM; it is often useful to see which example sequences have low scores, since this can be a tip that those sequences are garbage.

The scores reported by hmms are in bits of information. Specifically, they are log-odds scores: the log of the ratio of the probability of the sequence given the model and the probability of the sequence given a simple random sequence model. This score is related to the statistical significance of the alignment. A score of zero is marginal; according to the model's statistics, it's 50% likely that the alignment is a real match to the model, and 50% likely that it's not. The higher the score, the better; a score of 100 means that it is 2^100-fold more likely that the sequence is a match to the model than not. In practice, a database contains many more unrelated sequences than related ones, so the actual score required for statistical significance is somewhat higher than zero -- as a rule of thumb for protein database searches, don't trust scores lower than the log2 of the number of seqs in the database). This is 16 bits for our current SWIR5 composite protein database of 57,000 sequences. See the User Guide for more details.

hmms also includes some additional options that enable you to sample suboptimal alignments in addition to the optimal alignment. Fancy alignment output is toggled on when you ask for suboptimal alignments. -S asks for suboptimal alignments (one by default). -N <num> sets the number of alignments to sample. -K sets the kT temperature factor for the sampling; 1.0 is the default, where alignments are sampled according to their actual probability. Set kT higher for more randomized alignments, lower for less suboptimal alignments. The suboptimal alignment code is the same as is used for simulated annealing. See documentation on simulated annealing in the user's guide and the hmmt man page for more details.

Note the differences between the different HMM searching programs. hmms looks for a global alignment of HMM to sequences (Needleman/Wunsch style); overhangs of unmatches sequence are not permitted, and the full model must be matched. hmmls looks for one or more local alignments of the full model to a subsequence of each database sequence; unmatches sequence overhangs are allowed. hmmsw looks for the best fragmentary match of a subsequence to part of the model (Smith/Waterman style). hmmfs looks for multiple non-overlapping matches of subsequences to parts of the model (modified multiple-hit Smith/Waterman). hmms is useful for scoring or detecting whole proteins with complete models; hmmls is useful for scoring or detecting intact domains in protein sequences or complete repeats in nucleic acid sequences; hmmsw is useful for general protein database searching, allowing for possible incomplete matches to a model; hmmfs is useful for general nucleic acid database searching or for scoring/detecting domains in multidomain proteins, allowing for multiple non-overlapping matches per sequence.

OPTIONS

-h

Print short usage and help info for the program.

-q

quiet -- suppress the verbose banner. Useful for piping the output of hmmfs into another program or script.

-r <rfile>

Read the random sequence model from <rfile>. This model is used as the null hypothesis for calculating log-odds alignment scores.

-t <thresh>

Report only matches above a score of <thresh> bits. This is set to zero by default. Either negative or positive thresholds are acceptable.

-F

For each hit, print a "fancy" BLAST-style representation of the alignment to the model. Three lines are shown; a line for the model consensus, a line for the matched positions, and a line for the sequence. In the model consensus line, upper-case letters represent strong consensus positions, lower-case letters represent the best identity at a weak consensus position. (Strong and weak are arbitrarily defined; for protein models, log-odds symbol scores above 2.0 bits are called "strong" consensus.) On the match line, letters represent exact matches to the highest scoring possible residue according to the HMM, and +'s represent matches to positive-scoring residues.

-K <kT>

Sets the temperature (degree of suboptimality) for suboptimal sampling. Very high kT (> 5) produces essentially random alignments. kT=1.0 samples alignments according to their actual probability given the model. kT = 0.0 ("absolute zero") produces the optimal alignment. Default is 1.0. Only has effect if -S is also toggled.

-N <num>

Set the number of suboptimal alignments to sample. Default is 1. Only has effect if -S is also toggled.

-S

Toggles suboptimal alignment sampling on, in addition to seeing the optimal alignment.

Individual man pages: hmma(l), hmmb(l), hmme(l), hmmfs(l), hmmls(l), hmmsw(l), hmmt(l), hmm-convert(l)

User guide and tutorial: Userguide.ps

BUGS

Not very tolerant of errors on the command line.

NOTES

Sean Eddy
Dept. of Genetics, Washington Univ. School of Medicine 660 S. Euclid Box 8232
St Louis, MO 63110 USA
Phone: 1-314-362-7666
FAX : 1-314-362-2985

Email: eddy@genetics.wustl.edu

Table of Contents

• NAME
• SYNOPSIS
• DESCRIPTION
• OPTIONS
• SEE ALSO
• BUGS
• NOTES