Datasets:

mims-harvard
/

MedeaDB

Error code:   InfoError
Exception:    ReadTimeout
Message:      (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 62b285d8-5065-4242-86bd-ec8b0e029b3a)')
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 223, in compute_first_rows_from_streaming_response
                  info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
                  builder = load_dataset_builder(
                            ^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1132, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
                  ).get_module()
                    ^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 632, in get_module
                  data_files = DataFilesDict.from_patterns(
                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 689, in from_patterns
                  else DataFilesList.from_patterns(
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 592, in from_patterns
                  origin_metadata = _get_origin_metadata(data_files, download_config=download_config)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 506, in _get_origin_metadata
                  return thread_map(
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/tqdm/contrib/concurrent.py", line 69, in thread_map
                  return _executor_map(ThreadPoolExecutor, fn, *iterables, **tqdm_kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/tqdm/contrib/concurrent.py", line 51, in _executor_map
                  return list(tqdm_class(ex.map(fn, *iterables, chunksize=chunksize), **kwargs))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/tqdm/std.py", line 1169, in __iter__
                  for obj in iterable:
                             ^^^^^^^^
                File "/usr/local/lib/python3.12/concurrent/futures/_base.py", line 619, in result_iterator
                  yield _result_or_cancel(fs.pop())
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/concurrent/futures/_base.py", line 317, in _result_or_cancel
                  return fut.result(timeout)
                         ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/concurrent/futures/_base.py", line 456, in result
                  return self.__get_result()
                         ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
                  raise self._exception
                File "/usr/local/lib/python3.12/concurrent/futures/thread.py", line 59, in run
                  result = self.fn(*self.args, **self.kwargs)
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/data_files.py", line 485, in _get_single_origin_metadata
                  resolved_path = fs.resolve_path(data_file)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
                  repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
                                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
                  self._api.repo_info(
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 2816, in repo_info
                  return method(
                         ^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 2673, in dataset_info
                  r = get_session().get(path, headers=headers, timeout=timeout, params=params)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 602, in get
                  return self.request("GET", url, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 589, in request
                  resp = self.send(prep, **send_kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 703, in send
                  r = adapter.send(request, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 96, in send
                  return super().send(request, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/requests/adapters.py", line 690, in send
                  raise ReadTimeout(e, request=request)
              requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 62b285d8-5065-4242-86bd-ec8b0e029b3a)')

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MEDEA-DB

This database contains curated datasets and pre-trained model weights across multiple domains of tools leveraged by Medea, including:

Disease-gene associations and annotations (ChEMBL, etc.)
Protein-protein interaction networks & Multi-scale gene/protein embeddings (PINNACLE, TranscriptFormer, etc.)
Co-dependency statistics for disease gene pair (Chronos gene-effect profiles from DepMap 24Q2 CRISPR)
Immunotherapy response prediction models (COMPASS pretrain checkpoint)

Available Data & Resources

1. Gene/Protein Embeddings

PINNACLE Embeddings (`pinnacle_embeds/`)

Model: PINNACLE
Files:
- pinnacle_protein_embed.pth: Protein-level embeddings with cell type specificity
- pinnacle_mg_embed.pth: Meta-graph level embeddings on cellular interactions and tissue hierarchy
- ppi_embed_dict.pth: PPI-based embeddings
- pinnacle_labels_dict.txt: Gene/protein labels
Config Names: pinnacle_protein_embed, labels_dict
Format: PyTorch tensors

Transcriptformer Embeddings (`transcriptformer_embedding/`)

Model: Transcriptformer
Structure:
- embedding_generation/: Scripts for generating contextual gene embeddings (CGE)
- embedding_store/: Pre-computed embeddings (138 .npy files)
- processor/: Data processing utilities
Format: NumPy arrays, compressed archives

2. Drug & Target Data

ChEMBL Evidence (`sourceId_chembl_evidence/`)

Format: JSON (200 files)
Content: Drug-target evidence from ChEMBL database
Config Name: sourceId_chembl_evidence

3. Gene Dependency & Correlation Data

DepMap 24Q2 (`depmap_24q2/`)

Release: DepMap Public 24Q2
Files:
- corr_matrix.npy: Gene correlation matrix
- p_val_matrix.npy: Statistical significance values
- p_adj_matrix.npy: Adjusted p-values (multiple testing correction)
- gene_correlations.h5: HDF5 format correlations
- gene_idx_array.npy: Gene index mappings
- gene_names.txt: Gene identifiers

4. Immunotherapy Response Prediction Models

COMPASS Checkpoints (`immune-compass/checkpoint/`)

Model: COMPASS
Checkpoints:
- pretrainer.pt: Pre-trained base model checkpoint
- pft_leave_IMVigor210.pt: Leave-one-cohort-out (IMVigor210) fintuned checkpoint

Data Sources & Citations

Please cite the original sources when using specific datasets or models.

License

This dataset is released under the Apache license 2.0.

Downloads last month: 6

Size of the auto-converted Parquet files:

60.6 MB

Number of rows:

596,593