fix

multi_omics_transcript_expression.py

@@ -29,7 +29,7 @@ Task Specific Handlers:
 -------------------------------------------------------------------------------------------
 """
 
-logger = logging.getLogger("multi_omics_bulk_rna")
+logger = logging.getLogger("multi_omics_transcript_expression")
 logger.setLevel("INFO")
 
 
@@ -123,7 +123,7 @@ class GenomicLRATaskHandler(ABC):
 
 class TranscriptExpressionHandler(GenomicLRATaskHandler):
     """
-    Handler for the Bulk RNA Expression task.
+    Handler for the Transcript Expression task.
     """
 
     DEFAULT_LENGTH = 200000
@@ -136,7 +136,7 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
         **kwargs,
     ):
         """
-        Creates a new handler for the Bulk RNA Expression Prediction Task.
+        Creates a new handler for the Transcrpt Expression Prediction Task.
         Args:
             sequence_length: Length of the sequence around the TSS_CAGE start site
         Instance Vars:
@@ -160,7 +160,7 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
 
     def get_info(self, description: str) -> DatasetInfo:
         """
-        Returns the DatasetInfor for the Bulk RNA Expression dataset. Each example
+        Returns the DatasetInfor for the Transcript Expression dataset. Each example
         includes a genomic sequence and a list of label values.
         """
         features = datasets.Features(
@@ -186,7 +186,7 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
     def split_generators(self, dl_manager, cache_dir_root):
         """
         Separates files by split and stores filenames in instance variables.
-        The Bulk RNA Expression dataset requires the reference hg19 genome, coordinate
+        The Transcript Expression dataset requires the reference hg19 genome, coordinate
         csv file,and label csv file to be saved.
         """
         # Manually download the reference genome since there are difficulties when streaming
@@ -196,11 +196,11 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
         self.reference_genome = Fasta(reference_genome_file, one_based_attributes=False)
 
         self.coordinate_csv_file = dl_manager.download_and_extract(
-            "bulk_rna_expression/transcript_coordinates.csv"
+            "transcript_expression/transcript_coordinates.csv"
         )
 
         self.labels_csv_file = dl_manager.download_and_extract(
-            "bulk_rna_expression/rna_expression_values.csv"
+            "transcript_expression/rna_expression_values.csv"
         )
 
         return super().split_generators(dl_manager, cache_dir_root)
@@ -217,9 +217,7 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
 
         key = 0
         for idx, coordinates_row in coordinates_split_df.iterrows():
-            start = (
-                coordinates_row["position"] - 1
-            )  # -1 since vcf coords are 1-based
+            start = coordinates_row["position"] - 1  # -1 since vcf coords are 1-based
 
             chromosome = coordinates_row["chr"]
             labels_row = coordinates_row.loc[idx].values[2:]
@@ -257,7 +255,6 @@ Dataset for benchmark of genomic deep learning models.
 """
 
 
-
 # define dataset configs
 class GenomicsLRAConfig(datasets.BuilderConfig):
     """