lgonzalez1 commited on
Commit
8116cdb
·
1 Parent(s): 9ddea85
Files changed (1) hide show
  1. multi_omics_transcript_expression.py +28 -20
multi_omics_transcript_expression.py CHANGED
@@ -154,7 +154,8 @@ class GenomicLRATaskHandler(ABC):
154
  name=datasets.Split.TEST, gen_kwargs={"handler": self, "split": "test"}
155
  ),
156
  datasets.SplitGenerator(
157
- name=datasets.Split.VALIDATION, gen_kwargs={"handler": self, "split": "test"}
 
158
  ),
159
  ]
160
 
@@ -219,8 +220,8 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
219
  Handler for the Transcript Expression task.
220
  """
221
 
222
- DEFAULT_LENGTH = 200000
223
- DEFAULT_FILTER_OUT_LENGTH = 196608
224
 
225
  def __init__(
226
  self,
@@ -238,7 +239,6 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
238
  coordinate_csv_file: The csv file that stores the coordinates and filename of the target
239
  labels_csv_file: The csv file that stores the labels with one sample per row.
240
  sequence_length: Sequence length for this handler.
241
- expression_method: To specify if user wants to use TPMs instead of read
242
  counts.
243
  """
244
  self.reference_genome = None
@@ -246,7 +246,6 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
246
  self.labels_csv_file = None
247
  self.sequence_length = sequence_length
248
  self.filter_out_sequence_length = filter_out_sequence_length
249
- self.expression_method = expression_method
250
 
251
  if filter_out_sequence_length is not None:
252
  assert isinstance(filter_out_sequence_length, int)
@@ -266,6 +265,10 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
266
  "DNA": datasets.Value("string"),
267
  # list of expression values in each tissue
268
  "labels": datasets.Sequence(datasets.Value("float32")),
 
 
 
 
269
  "labels_name": datasets.Sequence(datasets.Value("string")),
270
  # chromosome number
271
  "chromosome": datasets.Value(dtype="string"),
@@ -297,18 +300,12 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
297
  )
298
  self.reference_genome = Fasta(reference_genome_file, one_based_attributes=False)
299
 
300
- if self.expression_method == "tpm":
301
- self.df_csv_file = dl_manager.download_and_extract(
302
- "transcript_expression/GTEx_final_tpm_multiomics_fix.csv"
303
- )
304
- elif self.expression_method == "read_counts_old":
305
- self.df_csv_file = dl_manager.download_and_extract(
306
- "transcript_expression/GTEx_v1_multiomics.csv"
307
- )
308
- elif self.expression_method == "read_counts":
309
- self.df_csv_file = dl_manager.download_and_extract(
310
- "transcript_expression/GTEx_read_counts_multiomics.csv"
311
- )
312
 
313
  return super().split_generators(dl_manager, cache_dir_root)
314
 
@@ -324,12 +321,18 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
324
 
325
  split_df = df.loc[df["split"] == split]
326
 
 
 
 
 
 
 
327
  key = 0
328
  for idx, coordinates_row in split_df.iterrows():
329
  negative_strand = coordinates_row["strand"] == "-"
330
 
331
  if negative_strand:
332
- start = coordinates_row["end"] - 1
333
  else:
334
  start = coordinates_row["start"] - 1 # -1 since vcf coords are 1-based
335
 
@@ -342,12 +345,17 @@ class TranscriptExpressionHandler(GenomicLRATaskHandler):
342
  negative_strand=negative_strand,
343
  filter_out_sequence_length=self.filter_out_sequence_length,
344
  )
 
345
  if padded_sequence:
346
  yield key, {
347
- "transcript_id":coordinates_row["transcript_id_gtex"],
348
- "gene_id":coordinates_row["gene_id_gtex"],
349
  "labels_name": labels_name,
350
  "labels": labels_row.to_numpy(),
 
 
 
 
351
  "DNA": standardize_sequence(padded_sequence),
352
  "chromosome": re.sub("chr", "", chromosome),
353
  "RNA": coordinates_row["RNA"],
 
154
  name=datasets.Split.TEST, gen_kwargs={"handler": self, "split": "test"}
155
  ),
156
  datasets.SplitGenerator(
157
+ name=datasets.Split.VALIDATION,
158
+ gen_kwargs={"handler": self, "split": "test"},
159
  ),
160
  ]
161
 
 
220
  Handler for the Transcript Expression task.
221
  """
222
 
223
+ DEFAULT_LENGTH = 200_000
224
+ DEFAULT_FILTER_OUT_LENGTH = 196_608
225
 
226
  def __init__(
227
  self,
 
239
  coordinate_csv_file: The csv file that stores the coordinates and filename of the target
240
  labels_csv_file: The csv file that stores the labels with one sample per row.
241
  sequence_length: Sequence length for this handler.
 
242
  counts.
243
  """
244
  self.reference_genome = None
 
246
  self.labels_csv_file = None
247
  self.sequence_length = sequence_length
248
  self.filter_out_sequence_length = filter_out_sequence_length
 
249
 
250
  if filter_out_sequence_length is not None:
251
  assert isinstance(filter_out_sequence_length, int)
 
265
  "DNA": datasets.Value("string"),
266
  # list of expression values in each tissue
267
  "labels": datasets.Sequence(datasets.Value("float32")),
268
+ "m_t": datasets.Sequence(datasets.Value("float32")),
269
+ "sigma_t": datasets.Sequence(datasets.Value("float32")),
270
+ "m_g": datasets.Sequence(datasets.Value("float32")),
271
+ "sigma_g": datasets.Sequence(datasets.Value("float32")),
272
  "labels_name": datasets.Sequence(datasets.Value("string")),
273
  # chromosome number
274
  "chromosome": datasets.Value(dtype="string"),
 
300
  )
301
  self.reference_genome = Fasta(reference_genome_file, one_based_attributes=False)
302
 
303
+ self.df_csv_file = dl_manager.download_and_extract(
304
+ "transcript_expression/GTEx_final_tpm_multiomics_fix.csv"
305
+ )
306
+ self.normalization_values_csv_file = dl_manager.download_and_extract(
307
+ "transcript_expression/normalization_values.csv"
308
+ )
 
 
 
 
 
 
309
 
310
  return super().split_generators(dl_manager, cache_dir_root)
311
 
 
321
 
322
  split_df = df.loc[df["split"] == split]
323
 
324
+ norm_values_df = pd.read_csv(self.normalization_values_csv_file)
325
+ m_t = norm_values_df["m_t"]
326
+ sigma_t = norm_values_df["sigma_t"]
327
+ m_g = norm_values_df["m_g"]
328
+ sigma_g = norm_values_df["sigma_g"]
329
+
330
  key = 0
331
  for idx, coordinates_row in split_df.iterrows():
332
  negative_strand = coordinates_row["strand"] == "-"
333
 
334
  if negative_strand:
335
+ start = coordinates_row["end"] - 1
336
  else:
337
  start = coordinates_row["start"] - 1 # -1 since vcf coords are 1-based
338
 
 
345
  negative_strand=negative_strand,
346
  filter_out_sequence_length=self.filter_out_sequence_length,
347
  )
348
+ fdsjog
349
  if padded_sequence:
350
  yield key, {
351
+ "transcript_id": coordinates_row["transcript_id_gtex"],
352
+ "gene_id": coordinates_row["gene_id_gtex"],
353
  "labels_name": labels_name,
354
  "labels": labels_row.to_numpy(),
355
+ "m_t": m_t.to_numpy(),
356
+ "sigma_t": sigma_t.to_numpy(),
357
+ "m_g": m_g.to_numpy(),
358
+ "sigma_g": sigma_g.to_numpy(),
359
  "DNA": standardize_sequence(padded_sequence),
360
  "chromosome": re.sub("chr", "", chromosome),
361
  "RNA": coordinates_row["RNA"],