bx.pwm.position_weight_matrix module
- class bx.pwm.position_weight_matrix.PositionWeightMatrix(id, rows, alphabet, background=None, score_correction=True)
Bases:
object- complementMap = {65: 84, 67: 71, 71: 67, 84: 65, 97: 116, 99: 103, 103: 99, 116: 97}
- corrected_probability_score(freq, base, i)
- correlation(otherwmx)
- information_base_content(base, i, counts)
- information_content_calculation(i, counts)
- max_correlation(otherwmx)
- parse_weight(weightString)
- pseudocount(base=None)
- pwm_score(base, i, freq, background=None)
- scaled(val)
- score_align(align, gapmask=None, byPosition=True)
- score_quantum_seq(seq)
- score_reverse_seq(seq)
- score_seq(seq)
- simple_probability(freq, base, i)
- slide_correlation(other)
- symbols = {'A': frozenset({'A'}), 'B': frozenset({'C', 'G', 'T'}), 'C': frozenset({'C'}), 'D': frozenset({'A', 'G', 'T'}), 'G': frozenset({'G'}), 'H': frozenset({'A', 'C', 'T'}), 'K': frozenset({'G', 'T'}), 'M': frozenset({'A', 'C'}), 'R': frozenset({'A', 'G'}), 'S': frozenset({'C', 'G'}), 'T': frozenset({'T'}), 'V': frozenset({'A', 'C', 'G'}), 'W': frozenset({'A', 'T'}), 'Y': frozenset({'C', 'T'})}
- to_count_matrix()
- to_matrix()
- class bx.pwm.position_weight_matrix.Reader(file, tfIds=None, name=None, format='basic', background=None, score_correction=True)
Bases:
objectIterate over all interesting weight matrices in a file
- close()
- read_as_basic()
- read_as_transfac()
- where()
- bx.pwm.position_weight_matrix.consensus_symbol(pattern)
- bx.pwm.position_weight_matrix.isnan(x)
- bx.pwm.position_weight_matrix.match_consensus(sequence, pattern)
- bx.pwm.position_weight_matrix.reverse_complement(nukes)
- bx.pwm.position_weight_matrix.rsquared(x, y)
- bx.pwm.position_weight_matrix.score_align_gaps(align)
- bx.pwm.position_weight_matrix.score_align_motif(align, motif, gapmask=None, byPosition=True)
- bx.pwm.position_weight_matrix.sum_of_squares(x, y=None)