Function: onehot_encoding

def onehot_encoding(sequences, pad_type= "after", pad_length= 0, n_jobs= 1) -> list[np.ndarray] | np.ndarray:

Description

Each nucleotide is encoded as follows:

• C= [1,0,0,0]
• G= [0,1,0,0]
• A= [0,0,1,0]
• T/U= [0,0,0,1]
• Other characters or gaps = [0,0,0,0]

See the About section for more details.

Parameters

Parameter	Type	Default	Description
sequences	any iterable containing str	Required	Sequences to encode, can also be dna-parser SequenceReader, pysam FastxFile or Biopython SeqIO.read objects.
pad_type	str	after	Whether to trim/pad at the front or at the back of the sequences. Options are before and after. This paramater is ignored if there is no padding
pad_length	int	0	Length for padding/trimming. -2 to pad to the longest sequence, -1 to trim to the shortest sequence, any positive integer for a fixed length.
n_jobs	int	1	number of threads used to encode the sequences in parallel. 0 to use all CPUs available.

Returns

Type	Description
list[numpy.ndarray] or numpy.ndarray	The encoded sequences. Returns a list of 2D numpy arrays if there is no trimming/padding, otherwise returns a 3D numpy array with the outermost dimension representing the sequences.

Examples

import dna_parser as dps

sequences= ["agt","acc"]
encoding= dps.onehot_encoding(sequences)
print(encoding)

# Output:
#[array([[0, 0, 1, 0],
#        [0, 1, 0, 0],
#        [0, 0, 0, 1]], dtype=int32),
# array([[0, 0, 1, 0],
#        [1, 0, 0, 0],
#        [1, 0, 0, 0]], dtype=int32)]


reader= dps.SequenceReader("path/to/file") # file with sequences agt, acc, attagc
encoding= dps.onehot_encoding(reader, pad_type="after", pad_length=-2) #pad after the sequences to the longest one
print(encoding)
print(encoding.shape)

# Output:
#[[[0 0 1 0]
#  [0 1 0 0]
#  [0 0 0 1]
#  [0 0 0 0]
#  [0 0 0 0]
#  [0 0 0 0]]
#
# [[0 0 1 0]
#  [1 0 0 0]
#  [1 0 0 0]
#  [0 0 0 0]
#  [0 0 0 0]
#  [0 0 0 0]]
#
# [[0 0 1 0]
#  [0 0 0 1]
#  [0 0 0 1]
#  [0 0 1 0]
#  [0 1 0 0]
#  [1 0 0 0]]]
#(3, 6, 4)