GCGC is a tool for feature processing on Biological Sequences.
GCGC is primarily intended to be used as part of a larger workflow inside Python.
To install via pip:
$ pip install gcgcIf you'd like to use code that helps gcgc's tokenizers integrate with common third party libraries, either install those packages separately, or use gcgc's extras.
$ pip install 'gcgc[hf]'The GCGC documentation is at gcgc.trenthauck.com, please see it for examples.
The easiest way to get started is to import the kmer tokenizer, configure it, then start tokenizing.
from gcgc import KmerTokenizer
kmer_tokenizer = KmerTokenizer(alphabet="unambiguous_dna")
encoded = kmer_tokenizer.encode("ATCG")
print(encoded)sample output:
[1, 6, 7, 8, 5, 2]
This output includes the "bos" token, the "eos" token, and the four nucleotide tokens in between.
You can go the other way and convert the integers to strings.
from gcgc import KmerTokenizer
kmer_tokenizer = KmerTokenizer(alphabet="unambiguous_dna")
decoded = kmer_tokenizer.decode(kmer_tokenizer.encode("ATCG"))
print(decoded)sample output:
['>', 'A', 'T', 'C', 'G', '<']
There's also the vocab for the kmer tokenizer.
from gcgc import KmerTokenizer
kmer_tokenizer = KmerTokenizer(alphabet="unambiguous_dna")
print(kmer_tokenizer.vocab.stoi)sample output:
{'|': 0, '>': 1, '<': 2, '#': 3, '?': 4, 'G': 5, 'A': 6, 'T': 7, 'C': 8}