def score_coded_seq_with_convolutional_filter(
coded_seq, filt, direction):
"""Score coded sequence using the convolutional filter filt.
input:
coded_seq: hot-one encoded DNA sequence (Nx4) where N is the number
of bases in the sequence.
filt : the convolutional filter (e.g. pwm) to score the model with.
direction: The direction to score the sequence in.
FWD: score the forward sequence
RC: score using the reverse complement of the filter
MAX: score in both diretions, and then return the maximum score
between the two directions
returns : Nx(BS_len-seq_len+1) numpy array with binding sites scores
"""
assert direction in ScoreDirection.__slots__
if direction == ScoreDirection.FWD:
return multichannel_convolve(
np.fliplr(np.flipud(coded_seq)), filt, mode='valid')
elif direction == ScoreDirection.RC:
return multichannel_convolve(
coded_seq, filt, mode='valid')
elif direction == ScoreDirection.MAX:
fwd_scores = multichannel_convolve(
np.fliplr(np.flipud(coded_seq)), filt, mode='valid')
rc_scores = multichannel_convolve(
coded_seq, filt, mode='valid')
# take the in-place maximum
return np.maximum(fwd_scores, rc_scores, fwd_scores)
assert False, 'Should be unreachable'
def score_coded_seq_with_convolutional_filter(coded_seq, filt):
"""Score coded sequence using the convolutional filter filt.
input:
coded_seq: hot-one encoded DNA sequence (Nx4) where N is the number
of bases in the sequence.
filt : the convolutional filter (e.g. pwm) to score the model with.
returns : Nx(BS_len-seq_len+1) numpy array with binding sites scores
"""
return multichannel_convolve(
np.fliplr(np.flipud(coded_seq)), filt, mode='valid')[::-1]
