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# Class Motif

source code

object --+
|
Motif

Known Subclasses:


A class representing sequence motifs.


 Instance Methods

 __getitem__(self, index) Returns the probability distribution over symbols at a given position, padding with background. source code

 __init__(self, alphabet=IUPACUnambiguousDNA()) x.__init__(...) initializes x; see help(type(x)) for signature source code

 __len__(self) return the length of a motif source code

 __str__(self, masked=False) string representation of a motif. source code

 _check_alphabet(self, alphabet) source code

 _check_length(self, len) source code

 _from_horiz_matrix(self, stream, letters=None, make_instances=False) reads a horizontal count matrix from stream and fill in the counts. source code

 _from_jaspar_pfm(self, stream, make_instances=False) reads the motif from Jaspar .pfm file source code

 _from_jaspar_sites(self, stream) reads the motif from Jaspar .sites file source code

 _from_vert_matrix(self, stream, letters=None, make_instances=False) reads a vertical count matrix from stream and fill in the counts. source code

 _pwm_calculate(self, sequence) source code

 _read(self, stream) Reads the motif from the stream (in AlignAce format). source code

 _to_fasta(self) FASTA representation of motif source code

 _to_horizontal_matrix(self, letters=None, normalized=True) Return string representation of the motif as a matrix. source code

 _to_jaspar_pfm(self) Returns the pfm representation of the motif... source code

 _to_transfac(self) Write the representation of a motif in TRANSFAC format... source code

 _to_vertical_matrix(self, letters=None) Return string representation of the motif as a matrix. source code

 _write(self, stream) writes the motif to the stream source code

 anticonsensus(self) returns the least probable pattern to be generated from this motif. source code

 consensus(self) Returns the consensus sequence of a motif. source code

 dist_dpq(self, other) Calculates the DPQ distance measure between motifs. source code

 dist_dpq_at(self, other, offset) calculates the dist_dpq measure with a given offset. source code

 dist_pearson(self, motif, masked=0) return the similarity score based on pearson correlation for the given motif against self. source code

 dist_pearson_at(self, motif, offset) source code

 dist_product(self, other) A similarity measure taking into account a product probability of generating overlaping instances of two motifs source code

 dist_product_at(self, other, offset) source code

 exp_score(self, st_dev=False) Computes expected score of motif's instance and its standard deviation source code

 format(self, format) Returns a string representation of the Motif in a given format source code

 ic(self) Method returning the information content of a motif. source code

 log_odds(self, laplace=True) returns the logg odds matrix computed for the set of instances source code

 make_counts_from_instances(self) Creates the count matrix for a motif with instances. source code

 Creates "fake" instances for a motif created from a count matrix. source code

 max_score(self) Maximal possible score for this motif. source code

 min_score(self) Minimal possible score for this motif. source code

 pwm(self, laplace=True) returns the PWM computed for the set of instances source code

 reverse_complement(self) Gives the reverse complement of the motif source code

 scanPWM(self, seq) Matrix of log-odds scores for a nucleotide sequence. source code

 score_hit(self, sequence, position, normalized=0, masked=0) give the pwm score for a given position source code

 search_instances(self, sequence) a generator function, returning found positions of instances of the motif in a given sequence source code

 search_pwm(self, sequence, normalized=0, masked=0, threshold=0.0, both=True) a generator function, returning found hits in a given sequence with the pwm score higher than the threshold source code

 weblogo(self, fname, format='PNG', **kwds) uses the Berkeley weblogo service to download and save a weblogo of itself source code

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __subclasshook__

 Properties

Inherited from object: __class__

 Method Details

### __getitem__(self, index)(Indexing operator)

source code
Returns the probability distribution over symbols at a given position, padding with background.

If the requested index is out of bounds, the returned distribution comes from background.



### __init__(self, alphabet=IUPACUnambiguousDNA())(Constructor)

source code
x.__init__(...) initializes x; see help(type(x)) for signature


Overrides: object.__init__
(inherited documentation)

### __len__(self)(Length operator)

source code
return the length of a motif

Please use this method (i.e. invoke len(m)) instead of refering to the m.length directly.



source code
string representation of a motif.


Overrides: object.__str__

### _from_jaspar_pfm(self, stream, make_instances=False)

source code

reads the motif from Jaspar .pfm file

The instances are fake, but the pwm is accurate.



### _from_jaspar_sites(self, stream)

source code

reads the motif from Jaspar .sites file

The instances and pwm are OK.



source code
Reads the motif from the stream (in AlignAce format).

the self.alphabet variable must be set beforehand.
If the last line contains asterisks it is used for setting mask



### _to_jaspar_pfm(self)

source code
Returns the pfm representation of the motif



### _to_transfac(self)

source code
Write the representation of a motif in TRANSFAC format



### dist_dpq(self, other)

source code
Calculates the DPQ distance measure between motifs.

It is calculated as a maximal value of DPQ formula (shown using LaTeX
markup, familiar to mathematicians):

\sqrt{\sum_{i=1}^{alignment.len()} \sum_{k=1}^alphabet.len() \
\{ m1[i].freq(alphabet[k])*log_2(m1[i].freq(alphabet[k])/m2[i].freq(alphabet[k])) +
m2[i].freq(alphabet[k])*log_2(m2[i].freq(alphabet[k])/m1[i].freq(alphabet[k]))
}

over possible non-spaced alignemts of two motifs.  See this reference:

D. M Endres and J. E Schindelin, "A new metric for probability
distributions", IEEE transactions on Information Theory 49, no. 7
(July 2003): 1858-1860.



### dist_dpq_at(self, other, offset)

source code

calculates the dist_dpq measure with a given offset.

offset should satisfy 0<=offset<=len(self)



source code

return the similarity score based on pearson correlation for the given motif against self.

We use the Pearson's correlation of the respective probabilities.



### format(self, format)

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Returns a string representation of the Motif in a given format

Currently supported fromats:
- jaspar-pfm : JASPAR Position Frequency Matrix
- transfac : TRANSFAC like files
- fasta : FASTA file with instances



### make_instances_from_counts(self)

source code
Creates "fake" instances for a motif created from a count matrix.

In case the sums of counts are different for different columnes, the
shorter columns are padded with background.



### max_score(self)

source code
Maximal possible score for this motif.

returns the score computed for the consensus sequence.



### min_score(self)

source code
Minimal possible score for this motif.

returns the score computed for the anticonsensus sequence.



### pwm(self, laplace=True)

source code

returns the PWM computed for the set of instances

if laplace=True (default), pseudocounts equal to self.background multiplied by self.beta are added to all positions.



### scanPWM(self, seq)

source code
Matrix of log-odds scores for a nucleotide sequence.

scans a nucleotide sequence and returns the matrix of log-odds
scores for all positions.

- the result is a one-dimensional list or numpy array
- the sequence can only be a DNA sequence
- the search is performed only on one strand



source code

sets the mask for the motif

The mask should be a string containing asterisks in the position of significant columns and spaces in other columns



### weblogo(self, fname, format='PNG', **kwds)

source code

uses the Berkeley weblogo service to download and save a weblogo of itself

requires an internet connection.
The parameters from **kwds are passed directly to the weblogo server.



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