Update genomics-long-range-benchmark.py

genomics-long-range-benchmark.py

@@ -527,4 +527,117 @@ class VariantEffectPredictionHandler(GenomicLRATaskHandler):
                     "alt_forward_sequence": standardize_sequence(alt_forward),
                     "distance_to_nearest_tss": distance
                 }
-                key += 1
+                key += 1
+
+"""
+--------------------------------------------------------------------------------------------
+Dataset loader:
+-------------------------------------------------------------------------------------------
+"""
+
+_DESCRIPTION = """
+Dataset for benchmark of genomic deep learning models. 
+"""
+
+_TASK_HANDLERS = {
+    "cage_prediction": CagePredictionHandler,
+    "bulk_rna_expression": BulkRnaExpressionHandler,
+    "variant_effect_gene_expression": VariantEffectPredictionHandler,
+}
+
+
+# define dataset configs
+class GenomicsLRAConfig(datasets.BuilderConfig):
+    """
+    BuilderConfig.
+    """
+
+    def __init__(self, *args, task_name: str, **kwargs):  # type: ignore
+        """BuilderConfig for the location tasks dataset.
+        Args:
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super().__init__()
+        self.handler = _TASK_HANDLERS[task_name](task_name=task_name,**kwargs)
+
+
+# DatasetBuilder
+class GenomicsLRATasks(datasets.GeneratorBasedBuilder):
+    """
+    Tasks to annotate human genome.
+    """
+
+    VERSION = datasets.Version("1.1.0")
+    BUILDER_CONFIG_CLASS = GenomicsLRAConfig
+
+    def _info(self) -> DatasetInfo:
+        return self.config.handler.get_info(description=_DESCRIPTION)
+
+    def _split_generators(
+            self, dl_manager: datasets.DownloadManager
+    ) -> List[datasets.SplitGenerator]:
+        """
+        Downloads data files and organizes it into train/test/val splits
+        """
+        return self.config.handler.split_generators(dl_manager, self._cache_dir_root)
+
+    def _generate_examples(self, handler, split):
+        """
+        Read data files and create examples(yield)
+        Args:
+            handler: The handler for the current task
+            split: A string in ['train', 'test', 'valid']
+        """
+        yield from handler.generate_examples(split)
+
+
+"""
+--------------------------------------------------------------------------------------------
+Global Utils:
+-------------------------------------------------------------------------------------------
+"""
+
+
+def standardize_sequence(sequence: str):
+    """
+    Standardizes the sequence by replacing all unknown characters with N and
+    converting to all uppercase.
+    Args:
+        sequence: genomic sequence to standardize
+    """
+    pattern = "[^ATCG]"
+    # all characters to upper case
+    sequence = sequence.upper()
+    # replace all characters that are not A,T,C,G with N
+    sequence = re.sub(pattern, "N", sequence)
+    return sequence
+
+
+def pad_sequence(chromosome, start, sequence_length, end=None, negative_strand=False):
+    """
+    Extends a given sequence to length sequence_length. If
+    padding to the given length is outside the gene, returns
+    None.
+    Args:
+        chromosome: Chromosome from pyfaidx extracted Fasta.
+        start: Start index of original sequence.
+        sequence_length: Desired sequence length. If sequence length is odd, the
+            remainder is added to the end of the sequence.
+        end: End index of original sequence. If no end is specified, it creates a
+            centered sequence around the start index.
+        negative_strand: If negative_strand, returns the reverse compliment of the sequence
+    """
+    if end:
+        pad = (sequence_length - (end - start)) // 2
+        start = start - pad
+        end = end + pad + (sequence_length % 2)
+    else:
+        pad = sequence_length // 2
+        end = start + pad + (sequence_length % 2)
+        start = start - pad
+
+    if start < 0 or end >= len(chromosome):
+        return
+    if negative_strand:
+        return chromosome[start:end].reverse.complement.seq
+    return chromosome[start:end].seq