Function: atomic_encoding
def atomic_encoding(sequences, pad_type= "after", pad_length= 0, n_jobs= 1) -> list[np.ndarray] | np.ndarray:
Description
Encodes sequences converting each nucleotide to its atomic number. Returns a list of 1D numpy arrays if there is no trimming/padding, otherwise returns a 2D numpy array with rows representing sequences.
- A= 70
- C= 58
- G= 78
- T/U= 66
- Other characters or gaps = 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 1D numpy arrays if there is no trimming/padding, otherwise returns a 2D numpy array with rows representing sequences. |
Examples
import dna_parser as dps
sequences= ["agt","acc"]
encoding= dps.atomic_encoding(sequences)
print(encoding)
# Output:
#[array([70, 78, 66], dtype=int32), array([70, 58, 58], dtype=int32)]
reader= dps.SequenceReader("path/to/file") # file with sequences agt, acc, attagc
encoding= dps.atomic_encoding(reader, pad_type="after", pad_length=-2) #pad after the sequences to the longest one
print(encoding)
print(encoding.shape)
# Output:
#[[70 78 66 0 0 0]
# [70 58 58 0 0 0]
# [70 66 66 70 78 58]]
#
#(3, 6)