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- bg_from_sequence(seq, ps)
- Estimates the background distribution of nucleotides
from seq. The pseudocount ps is added to all counts.
- count_log_odds(matrix, bg, ps, log_base=None)
- Calculates a log-odds matrix from a position frequency matrix
Returns:
The input PWM matrix transformed to log-odds scores.
The score for nucleotide N and position i is
log ( matrix[N][i] + ps * bg[N] ) / C[i]
- log ( bg[N] ),
where C[i] is the sum of terms
matrix[N][i] + ps * bg[N]
for all nucleotides N.
Parameters:
Obligatory:
matrix
Input PWM as a float or integer matrix.
bg
Normalised background distribution given as
a list of four floats.
ps
Multiplier for pseudocounts. If matrix is
a frequency matrix, you may want to
set this to zero.
Optional:
log_base
Base for logarithms. Defaults to natural
logarithm if None is given.
- flatbg(size=4)
- Creates a flat background distribution table
- load_matrix(filename)
- Loads a matrix from a file given.
Returns matrix as an array of arrays of numbers.
- max_score(matrix)
- Calculates a maximum score of matrix
- reverse_complement(matrix)
- Creates a reverse complement of PWM
- search(sequence, matrices, thresholds, bg=None, convert_log_odds=True, threshold_from_p=True, both_strands=False, log_base=None, pseudocount=1, algorithm='lf', q=7, combine=True)
- Finds position weight matrix matches in DNA sequence.
Returns:
An array of references to result arrays. There is one result
array for each matrix, in the same order as the input matrices.
Each result array is a list of tuples of position and score
given as: [(pos1, score1), (pos2, score2) ...]
Parameters:
Obligatory:
sequence
DNA sequence as python string object, containing characters
acgtACGT.
matrices
An array of matrices, each represented as a list of four
lists of equal length. These lists correspond the
frequencies or scores of the nucleotides A, C, G and T,
respectively.
thresholds
A number or a list of numbers, used as threshold values for
matrix scanning. If a single number is given, it is used
for all matrices; otherwise, there should be as many
threshold values as there are matrices.
Optional:
bg
Background distribution as an array of four doubles,
corresponding to the frequencies of A, C, G and T,
respectively. By default the background is estimated from
the sequence.
convert_log_odds
If True, assumes that the input matrices are frequency or
count matrices, and converts them to log-odds scoring
matrices using function count_log_odds; otherwise, treat
them as scoring matrices. Default True.
threshold_from_p
If True, assumes that thresholds are p-values and computes
the corresponding absolute threshold based on the matrix
using function threshold_from_p; otherwise the threshold
is used as a hard cut-off. Default True.
log_base
Base for logarithms used in log-odds computations. Relevant
if using convert_log_odds=True and threshold_from_p=False.
Defaults to natural logarithm if None is given.
pseudocount
Pseudocount used in log-odds conversion and added to
sequence symbol counts when estimating the background
from sequence. Default 1.
both_strands
Scans against reverse complement sequence in addition to
the input sequence. Hits on reverse complement are reported
at position [position - sequence_length], which is always
negative. The actual hit site for any hit is always
seq[pos, pos + matrix_length].
Default False.
Tuning parameters:
(Optional, do not affect the results, but can give minor
speed-ups in some cases. You can pretty much ignore these.)
algorithm
Selects the algorithm to use for scanning
"naive" naive algorithm
"pla" permutated lookahead algorithm
"supera" super alphabet algorithm.
- Good for long matrices (> 20)
"lf" lookahead filtration algorithm.
- Default algorithm in most cases.
- Sequence can be searched with multiple matrices
simultaneously.
q
An integer, used for fine-tuning "supera" and "lf" algorithms.
The default value 7 should be ok pretty much always, but can
be tuned to possibly slightly increase performance.
combine
True or False, determines whether "lf" algorithm combines all
matrices to a single scanning pass. Default True.
- threshold_from_p(matrix, bg, p)
- Calculates an absolute threshold from a probability value.
Returns:
A threshold value T such that the probability that
the distribution bg generates a sequence scoring
at least T on the input matrix is p.
- total_matches(matchArray)
- Calculates a total number of matches.
- transpose(matrix)
- Creates a transpose of matrix array
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