Update Genome_database.py

Genome_database.py

@@ -1,12 +1,13 @@
-from datasets import DatasetBuilder, GenerateMode
+import datasets
 from Bio import SeqIO
-from typing import Any, Dict, List, Tuple
 from Bio.SeqUtils import gc_fraction
+from typing import Any, Dict, List, Tuple
 import os
 import gzip
+import re
 
-class GenomeDataset(DatasetBuilder):
-    VERSION = datasets.Version("1.0.0")
+class GenomeDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.1.0")
     
     def _info(self):
         return datasets.DatasetInfo(
@@ -20,41 +21,45 @@ class GenomeDataset(DatasetBuilder):
                 "sequence": datasets.Value("string"),
                 "gc_content": datasets.Value("float"),
                 "translation_code": datasets.Value("string"),
+                "start_postion": datasets.Value("int32"),
+                "end_position": datasets.Value("int32"),
             })
         )
 
     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}
-          )
-      ]
+        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]]:
+        split_regex = re.compile('-')
         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
+                            collection_date = record.annotations.get('date', 'unknown')
+                            year = split_regex.split(collection_date)[-1] if '-' in collection_date else collection_date
                             for feature in record.features:
-                                if feature.type in ['rRNA', 'tRNA','CDS','tmRNA']:
+                                seq = feature.extract(record.seq)
+                                gc_content = gc_fraction(seq)
+                                start_position = int(feature.location.start)
+                                end_position = int(feature.location.end)
+                                if feature.type in ['rRNA', 'tRNA','CDS','tmRNA','mRNA','mat_peptide','sig_peptide','propeptide']:
                                     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'
@@ -64,20 +69,18 @@ class GenomeDataset(DatasetBuilder):
                                 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:
+                                    if feature.qualifiers.get('product') != ['']:
+                                        product = feature.qualifiers.get('product', ['NA'])[0]
+                                    else:
+                                        product = 'NA'
                                     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, 
@@ -87,5 +90,8 @@ class GenomeDataset(DatasetBuilder):
                                     'product': product, 
                                     'sequence': str(seq), 
                                     'gc_content': gc_content, 
-                                    'translation_code': translation
-                                }
+                                    'translation_code': translation,
+                                    'start_postion': start_position,
+                                    'end_position': end_position
+                                }
+