Files
D-SCRIPT/dscript/alphabets.py
2025-07-21 14:21:48 -04:00

126 lines
3.4 KiB
Python

import numpy as np
class Alphabet:
"""
From `Bepler & Berger <https://github.com/tbepler/protein-sequence-embedding-iclr2019>`_.
:param chars: List of characters in alphabet
:type chars: byte str
:param encoding: Mapping of characters to numbers [default: encoding]
:type encoding: np.ndarray
:param mask: Set encoding mask [default: False]
:type mask: bool
:param missing: Number to use for a value outside the alphabet [default: 255]
:type missing: int
"""
def __init__(self, chars, encoding=None, mask=False, missing=255):
self.chars = np.frombuffer(chars, dtype=np.uint8)
self.encoding = np.zeros(256, dtype=np.uint8) + missing
if encoding is None:
self.encoding[self.chars] = np.arange(len(self.chars))
self.size = len(self.chars)
else:
self.encoding[self.chars] = encoding
self.size = encoding.max() + 1
self.mask = mask
if mask:
self.size -= 1
def __len__(self):
return self.size
def __getitem__(self, i):
return chr(self.chars[i])
def encode(self, x):
"""
Encode a byte string into alphabet indices
:param x: Amino acid string
:type x: byte str
:return: Numeric encoding
:rtype: np.ndarray
"""
x = np.frombuffer(x, dtype=np.uint8)
return self.encoding[x]
def decode(self, x):
"""
Decode numeric encoding to byte string of this alphabet
:param x: Numeric encoding
:type x: np.ndarray
:return: Amino acid string
:rtype: byte str
"""
string = self.chars[x]
return string.tobytes()
def unpack(self, h, k):
"""unpack integer h into array of this alphabet with length k"""
n = self.size
kmer = np.zeros(k, dtype=np.uint8)
for i in reversed(range(k)):
c = h % n
kmer[i] = c
h = h // n
return kmer
def get_kmer(self, h, k):
"""retrieve byte string of length k decoded from integer h"""
kmer = self.unpack(h, k)
return self.decode(kmer)
DNA = Alphabet(b"ACGT")
class Uniprot21(Alphabet):
"""
Uniprot 21 Amino Acid Encoding.
From `Bepler & Berger <https://github.com/tbepler/protein-sequence-embedding-iclr2019>`_.
"""
def __init__(self, mask=False):
chars = b"ARNDCQEGHILKMFPSTWYVXOUBZ"
encoding = np.arange(len(chars))
encoding[21:] = [11, 4, 20, 20] # encode 'OUBZ' as synonyms
super().__init__(chars, encoding=encoding, mask=mask, missing=20)
class SDM12(Alphabet):
"""
A D KER N TSQ YF LIVM C W H G P
See https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2732308/#B33
"Reduced amino acid alphabets exhibit an improved sensitivity and selectivity in fold assignment"
Peterson et al. 2009. Bioinformatics.
"""
def __init__(self, mask=False):
chars = b"ADKNTYLCWHGPXERSQFIVMOUBZ"
groups = [
b"A",
b"D",
b"KERO",
b"N",
b"TSQ",
b"YF",
b"LIVM",
b"CU",
b"W",
b"H",
b"G",
b"P",
b"XBZ",
]
groups = {c: i for i in range(len(groups)) for c in groups[i]}
encoding = np.array([groups[c] for c in chars])
super().__init__(chars, encoding=encoding, mask=mask)
SecStr8 = Alphabet(b"HBEGITS ")