Bio.motifs.matrix module

Support for various forms of sequence motif matrices.

Implementation of frequency (count) matrices, position-weight matrices, and position-specific scoring matrices.

class Bio.motifs.matrix.GenericPositionMatrix(alphabet, values)

Bases: dict

Base class for the support of position matrix operations.

__init__(alphabet, values): Initialize the class.

__str__(): Return a string containing nucleotides and counts of the alphabet in the Matrix.

__getitem__(key): Return the position matrix of index key.

property consensus: Return the consensus sequence.

property anticonsensus: Return the anticonsensus sequence.

property degenerate_consensus: Return the degenerate consensus sequence.

property gc_content: Compute the fraction GC content.

reverse_complement(): Compute reverse complement.

class Bio.motifs.matrix.FrequencyPositionMatrix(alphabet, values)

Bases: Bio.motifs.matrix.GenericPositionMatrix

Class for the support of frequency calculations on the Position Matrix.

normalize(pseudocounts=None)

Create and return a position-weight matrix by normalizing the counts matrix.

If pseudocounts is None (default), no pseudocounts are added to the counts.

If pseudocounts is a number, it is added to the counts before calculating the position-weight matrix.

Alternatively, the pseudocounts can be a dictionary with a key for each letter in the alphabet associated with the motif.

class Bio.motifs.matrix.PositionWeightMatrix(alphabet, counts)

Bases: Bio.motifs.matrix.GenericPositionMatrix

Class for the support of weight calculations on the Position Matrix.

__init__(alphabet, counts): Initialize the class.

log_odds(background=None)

Return the Position-Specific Scoring Matrix.

The Position-Specific Scoring Matrix (PSSM) contains the log-odds scores computed from the probability matrix and the background probabilities. If the background is None, a uniform background distribution is assumed.

class Bio.motifs.matrix.PositionSpecificScoringMatrix(alphabet, values)

Bases: Bio.motifs.matrix.GenericPositionMatrix

Class for the support of Position Specific Scoring Matrix calculations.

calculate(sequence)

Return the PWM score for a given sequence for all positions.

Notes:

the sequence can only be a DNA sequence
the search is performed only on one strand
if the sequence and the motif have the same length, a single number is returned
otherwise, the result is a one-dimensional numpy array

search(sequence, threshold=0.0, both=True, chunksize=10 ** 6)

Find hits with PWM score above given threshold.

A generator function, returning found hits in the given sequence with the pwm score higher than the threshold.

property max

Maximal possible score for this motif.

returns the score computed for the consensus sequence.

property min

Minimal possible score for this motif.

returns the score computed for the anticonsensus sequence.

property gc_content: Compute the GC-ratio.

mean(background=None): Return expected value of the score of a motif.

std(background=None): Return standard deviation of the score of a motif.

dist_pearson(other)

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

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

dist_pearson_at(other, offset): Return the similarity score based on pearson correlation at the given offset.

distribution(background=None, precision=10 ** 3): Calculate the distribution of the scores at the given precision.