multi-model-plant-genome-corpus.py

from typing import List
import datasets
from Bio import SeqIO
import os

_CITATION = ""
_HOMEPAGE = "https://www.ncbi.nlm.nih.gov/"
_LICENSE = "https://www.ncbi.nlm.nih.gov/home/about/policies/"
_CHUNK_LENGTHS = [510,]

def filter_fn(char: str) -> str:
    """
    Transforms any letter different from a base nucleotide into an 'N'.
    """
    if char in {'A', 'T', 'C', 'G'}:
        return char
    else:
        return 'N'
    
def clean_sequence(seq: str) -> str:
    """
    Process a chunk of DNA to have all letters in upper and restricted to
    A, T, C, G and N.
    """
    seq = seq.upper()
    seq = map(filter_fn, seq)
    seq = ''.join(list(seq))
    return seq
    
class PlantMultiSpeciesGenomesConfig(datasets.BuilderConfig):
    """BuilderConfig for the Plant Multi Species Pre-training Dataset."""
    def __init__(self, *args, chunk_length: int, overlap: int = 255, **kwargs):
        """BuilderConfig for the multi species genomes.
        Args:
            chunk_length (:obj:`int`): Chunk length.
            overlap: (:obj:`int`): Overlap in base pairs for two consecutive chunks (defaults to 100).
            **kwargs: keyword arguments forwarded to super.
        """
        super().__init__(
            *args,
            name=f'{chunk_length}bp',
            **kwargs,
        )
        self.chunk_length = chunk_length
        self.overlap = overlap

class PlantMultiSpeciesGenomes(datasets.GeneratorBasedBuilder):
    """Genomes from multiple plant species, filtered and split into chunks of consecutive nucleotides."""
    VERSION = datasets.Version("1.1.0")
    BUILDER_CONFIG_CLASS = PlantMultiSpeciesGenomesConfig
    BUILDER_CONFIGS = [PlantMultiSpeciesGenomesConfig(chunk_length=chunk_length) for chunk_length in _CHUNK_LENGTHS]
    DEFAULT_CONFIG_NAME = "510bp"
    
    def _info(self):
    
        features = datasets.Features(
            {
                "sequence": datasets.Value("string"),
                "description": datasets.Value("string"),
                "start_pos": datasets.Value("int32"),
                "end_pos": datasets.Value("int32"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )
    
    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
        filepaths_txt = dl_manager.download('plant_genome_file_names.txt')
    
        with open(filepaths_txt, 'r') as f:
            filepaths = [os.path.join("plant_genomes", filepath.rstrip()) for filepath in f]
    
        genome_files = dl_manager.download_and_extract(filepaths)
    
        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": genome_files, "chunk_length": self.config.chunk_length})
        ]
    
    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
    def _generate_examples(self, files, chunk_length):
        key = 0
        for file in files:
            with open(file, 'rt') as f:
                fasta_sequences = SeqIO.parse(f, 'fasta')
    
                for record in fasta_sequences:
                    sequence, description = str(record.seq), record.description
    
                    # clean chromosome sequence
                    sequence = clean_sequence(sequence)
                    seq_length = len(sequence)
    
                    # split into chunks
                    num_chunks = (seq_length - 2 * self.config.overlap) // chunk_length
    
                    if num_chunks < 1:
                        continue
    
                    sequence = sequence[:(chunk_length * num_chunks + 2 * self.config.overlap)]
                    seq_length = len(sequence)
    
                    for i in range(num_chunks):
                        # get chunk
                        start_pos = i * chunk_length
                        end_pos = min(seq_length, (i+1) * chunk_length + 2 * self.config.overlap)
                        chunk_sequence = sequence[start_pos:end_pos]
    
                        # yield chunk
                        yield key, {
                            'sequence': chunk_sequence,
                            'description': description,
                            'start_pos': start_pos,
                            'end_pos': end_pos,
                        }
                        key += 1