Function: dna_walk
def dna_walk(sequences, pad_type= "after", pad_length= 0, n_jobs= 1) -> list[np.ndarray] | np.ndarray:
Description
Each sequence is represented on a 2D grid, with its representation starting at coordinates (0,0). For each nucleotide in the sequence coordinates are updated to form a path as follows:
- A: x_{n+1}= x_{n}-1; y_{n+1}= y_{n}
- C: x_{n+1}= x_{n}; y_{n+1}= y_{n}-1
- G: x_{n+1}= x_{n}; y_{n+1}= y_{n}+1
- T/U: x_{n+1}= x+1; y_{n+1}= y_{n}
- Other characters or gaps: x_{n+1}= x_{n}; y_{n+1}= y_{n}
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 outer dimension representing sequences. |
Examples
import dna_parser as dps
sequences= ["agt","acc"]
encoding= dps.dna_walk(sequences)
print(encoding)
# Output:
#[array([[-1, 0],
# [-1, 1],
# [ 0, 1]], dtype=int32),
# array([[-1, 0],
# [-1, -1],
# [-1, -2]], dtype=int32)]
reader= dps.SequenceReader("path/to/file") # file with sequences agt, acc, attagc
encoding= dps.dna_walk(reader, pad_type="after", pad_length=-2) #pad after the sequences to the longest one
print(encoding)
print(encoding.shape)
# Output:
#[[[-1 0]
# [-1 1]
# [ 0 1]
# [ 0 1]
# [ 0 1]
# [ 0 1]]
#
# [[-1 0]
# [-1 -1]
# [-1 -2]
# [-1 -2]
# [-1 -2]
# [-1 -2]]
#
# [[-1 0]
# [ 0 0]
# [ 1 0]
# [ 0 0]
# [ 0 1]
# [ 0 0]]]
#(3, 6, 2)