Create Genome_database.py

Genome_database.py

@@ -0,0 +1,90 @@
+from datasets import DatasetBuilder, GenerateMode
+from Bio import SeqIO
+from typing import Any, Dict, List, Tuple
+from Bio.SeqUtils import gc_fraction
+import os
+import gzip
+
+class GenomeDataset(DatasetBuilder):
+    VERSION = datasets.Version("1.0.0")
+    
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features({
+                "DNA_id": datasets.Value("string"),
+                "organism": datasets.Value("string"),
+                "year": datasets.Value("string"),
+                "region_type": datasets.Value("string"),
+                "specific_class": datasets.Value("string"),
+                "product": datasets.Value("string"),
+                "sequence": datasets.Value("string"),
+                "gc_content": datasets.Value("float"),
+                "translation_code": datasets.Value("string"),
+            })
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+    downloaded_files = dl_manager.download_and_extract('https://ftp.ncbi.nih.gov/genbank/') 
+    train_files = downloaded_files[:int(len(downloaded_files) * 0.8)] # first 80% for training
+    test_files = downloaded_files[int(len(downloaded_files) * 0.8):]  # last 20% for testing
+
+    return [
+        datasets.SplitGenerator(
+            name=datasets.Split.TRAIN,
+            gen_kwargs={"filepaths": train_files}
+        ),
+        datasets.SplitGenerator(
+            name=datasets.Split.TEST,
+            gen_kwargs={"filepaths": test_files}
+        )
+    ]
+
+    def _generate_examples(self, filepaths: List[str]) -> Tuple[str, Dict[str, Any]]:
+        for filepath in filepaths:
+            if filepath.endswith(".seq.gz"):
+                with gzip.open(filepath, 'rt') as handle:
+                    for record in SeqIO.parse(handle, "genbank"):
+                        if 'molecule_type' in record.annotations and record.annotations['molecule_type'] == 'DNA':
+                            organism = record.annotations.get('organism', 'unknown')
+                            collection_date = record.annotations.get('date', 'unkown')
+                            year = collection_date.split('-')[-1] if '-' in collection_date else collection_date
+                            for feature in record.features:
+                                if feature.type in ['rRNA', 'tRNA','CDS','tmRNA']:
+                                    region_type = 'coding'
+                                    product = feature.qualifiers.get('product', ['Unknown'])[0]
+                                    seq = feature.extract(record.seq)
+                                    gc_content = gc_fraction(seq)
+                                    if feature.type == 'CDS':
+                                        translation = feature.qualifiers.get('translation', [''])[0]
+                                        specific_class = 'Protein'
+                                    else:
+                                        translation = 'NA'
+                                        specific_class = feature.type
+                                elif feature.type == 'regulatory':
+                                    region_type = feature.type
+                                    specific_class = feature.qualifiers.get('regulatory_class', ['regulatory'])[0]
+                                    seq = feature.extract(record.seq)
+                                    gc_content = gc_fraction(seq)
+                                    #gene_tag = feature.qualifiers.get('locus_tag', [''])[0]
+                                    translation = 'NA'
+                                    product = 'NA'
+                                elif feature.type == 'gene':
+                                    continue
+                                else:
+                                    region_type = feature.type
+                                    seq = feature.extract(record.seq)
+                                    gc_content = gc_fraction(seq)
+                                    specific_class = 'NA'
+                                    translation = 'NA'
+                                    product = 'NA'
+                                yield record.id, {
+                                    'DNA_id': record.id,
+                                    'organism': organism, 
+                                    'year': year, 
+                                    'region_type': region_type, 
+                                    'specific_class': specific_class, 
+                                    'product': product, 
+                                    'sequence': str(seq), 
+                                    'gc_content': gc_content, 
+                                    'translation_code': translation
+                                }