Create or edit hidden Markov model (HMM) profile structure
Model
= hmmprofstruct(Length
)
Model
= hmmprofstruct(Length
, Field1
, Field1Value
, Field2
, Field2Value
,
...)
NewModel
= hmmprofstruct(Model
, Field1
, Field1Value
, Field2
, Field2Value
,
...)
Length  Number of match states in the model. 
Model  MATLAB^{®} structure containing fields for the parameters
of an HMM profile created with the hmmprofstruct function. 
Field  Character vector or string containing a field name in the structure
Model . See the table below for field names. 
FieldValue  Value associated with Field . See
the table below for descriptions. 
Model  MATLAB structure containing fields for the parameters of an HMM profile. 
returns Model
= hmmprofstruct(Length
)Model
,
a MATLAB structure containing fields for the parameters of an
HMM profile. Length
specifies the number
of match states in the model. All other required parameters are set
to the default values.
returns an HMM profile structure using the specified
parameters. All other required parameters are set to default values.Model
= hmmprofstruct(Length
, Field1
, Field1Value
, Field2
, Field2Value
,
...)
returns an updated HMM profile structure using the
specified parameters. All other parameters are taken from the input NewModel
= hmmprofstruct(Model
, Field1
, Field1Value
, Field2
, Field2Value
,
...)Model
.
The MATLAB structure Model
contains
the following fields, which are the required and optional parameters
of an HMM profile. All probability values are in the [0 1] range.
Field  Description 

ModelLength  Integer specifying the length of the profile (number of MATCH states). 
Alphabet  Character vector or string specifying the alphabet used in the model. Choices are
'AA' (default) or 'NT' . Note

MatchEmission  Symbol emission probabilities in the MATCH states. Either of the following: 
InsertEmission  Symbol emission probabilities in the INSERT state. Either of the following: 
NullEmission  Symbol emission probabilities in the MATCH and INSERT states for the NULL model. Either of the following: NoteThe NULL model is used to compute the logodds ratio at every state and avoid overflow when propagating the probabilities through the model. NoteNULL probabilities are also known as the background probabilities. 
BeginX  BEGIN state transition probabilities. Format
is a 1by [B>D1 B>M1 B>M2 B>M3 .... B>Mend] NoteIf necessary, sum(Model.BeginX) = 1 For fragment profiles: sum(Model.BeginX(3:end)) = 0 Default is 
MatchX  MATCH state transition probabilities. Format
is a 4by [M1>M2 M2>M3 ... M[end1]>Mend; M1>I1 M2>I2 ... M[end1]>I[end1]; M1>D2 M2>D3 ... M[end1]>Dend; M1>E M2>E ... M[end1]>E ] NoteIf necessary, sum(Model.MatchX) = [ 1 1 ... 1 ] For fragment profiles: sum(Model.MatchX(4,:)) = 0 Default is 
InsertX  INSERT state transition probabilities. Format
is a 2by [ I1>M2 I2>M3 ... I[end1]>Mend; I1>I1 I2>I2 ... I[end1]>I[end1] ] NoteIf necessary, sum(Model.InsertX) = [ 1 1 ... 1 ] Default is 
DeleteX  DELETE state transition probabilities. Format
is a 2by [ D1>M2 D2>M3 ... D[end1]>Mend ; D1>D2 D2>D3 ... D[end1]>Dend ] NoteIf necessary, sum(Model.DeleteX) = [ 1 1 ... 1 ] Default is 
FlankingInsertX  Flanking insert states (N and C) used for LOCAL profile alignment. Format is a 2by2 matrix: [N>B C>T ; N>N C>C] NoteIf necessary, sum(Model.FlankingInsertsX) = [1 1] NoteTo force global alignment use: Model.FlankingInsertsX = [1 1; 0 0] Default is 
LoopX  Loop states transition probabilities used for multiple hits alignment. Format is a 2by2 matrix: [E>C J>B ; E>J J>J] NoteIf necessary, sum(Model.LoopX) = [1 1] Default is 
NullX  Null transition probabilities used to provide scores with logodds values also for state transitions. Format is a 2by1 column vector: [G>F ; G>G] NoteIf necessary, sum(Model.NullX) = 1 Default is 
IDNumber  Optional. Userassigned identification number. 
Description  Optional. Userassigned description of the model. 
An HMM profile model is a common statistical tool for modeling structured sequences composed of symbols. These symbols include randomness in both the output (emission of symbols) and the state transitions of the process. Markov models are generally represented by state diagrams.
The following figure is a state diagram for an HMM profile of length four. INSERT, MATCH, and DELETE states are in the center section.
INSERT state represents the excess of one or more symbols in the target sequence that are not included in the profile.
MATCH state means that the target sequence is aligned to the profile at the specific location.
DELETE state represents a gap or symbol absence in the target sequence (also known as a silent state because it does not emit any symbols).
Flanking states (S
, N
, B
, E
, C
, T
)
are used for proper modeling of the ends of the sequence, either for
global, local or fragment alignment of the profile. S
, B
, E
,
and T
are silent, while N
and C
are
used to insert symbols at the flanks.
Create an HMM profile structure with 100 MATCH states, using the amino acid alphabet.
hmmProfile = hmmprofstruct(100,'Alphabet','AA') hmmProfile = ModelLength: 100 Alphabet: 'AA' MatchEmission: [100x20 double] InsertEmission: [100x20 double] NullEmission: [1x20 double] BeginX: [101x1 double] MatchX: [99x4 double] InsertX: [99x2 double] DeleteX: [99x2 double] FlankingInsertX: [2x2 double] LoopX: [2x2 double] NullX: [2x1 double]
Use the pfamhmmread
function
to create an HMM profile structure from pf00002.ls
,
a PFAM HMMformatted file included with the software.
hmm02 = pfamhmmread('pf00002.ls');
Modify the HMM profile structure to force a global alignment by setting the looping transition probabilities in the flanking insert states to zero.
hmm02 = hmmprofstruct(hmm02,'FlankingInsertX',[0 0;1 1]);
hmm02.FlankingInsertX
ans =
0 0
1 1
aacount
 basecount
 gethmmprof
 hmmprofalign
 hmmprofestimate
 hmmprofgenerate
 hmmprofmerge
 pfamhmmread
 showhmmprof