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Datasets:
luoyiming1991
/
screen-registry-v4-immune-contexts

Languages:
English
Tags:
genomics
encode
screen
ccre
regulatory-elements
immunology
License:
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
assembly: string
catalog: struct<path: string, sha256: string, size: int64>
  child 0, path: string
  child 1, sha256: string
  child 2, size: int64
ccre_count: int64
class_codes: struct<0: struct<description: string, label: string>, 1: struct<description: string, label: string>, (... 329 chars omitted)
  child 0, 0: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 1, 1: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 2, 2: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 3, 3: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 4, 4: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 5, 5: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 6, 6: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 7, 7: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
  child 8, 8: struct<description: string, label: string>
      child 0, description: string
      child 1, label: string
created_at: timestamp[s]
immune_matrix: struct<layout: string, path: string, sha256: string, shape: list<i
...
chars omitted)
  child 0, immune_biosamples: struct<call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, d (... 132 chars omitted)
      child 0, call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, dELS: int64, inactive (... 21 chars omitted)
          child 0, CA: int64
          child 1, CA-CTCF: int64
          child 2, CA-H3K4me3: int64
          child 3, CA-TF: int64
          child 4, PLS: int64
          child 5, dELS: int64
          child 6, inactive: int64
          child 7, pELS: int64
      child 1, observed_labels: list<item: string>
          child 0, item: string
      child 2, supported_but_unobserved_labels: list<item: string>
          child 0, item: string
  child 1, tissues: struct<call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, d (... 132 chars omitted)
      child 0, call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, dELS: int64, inactive (... 21 chars omitted)
          child 0, CA: int64
          child 1, CA-CTCF: int64
          child 2, CA-H3K4me3: int64
          child 3, CA-TF: int64
          child 4, PLS: int64
          child 5, dELS: int64
          child 6, inactive: int64
          child 7, pELS: int64
      child 1, observed_labels: list<item: string>
          child 0, item: string
      child 2, supported_but_unobserved_labels: list<item: string>
          child 0, item: string
to
{'artifacts': {'database': {'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}, 'members_tsv': {'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}}, 'assembly': Value('string'), 'audit_policy_sha256': Value('string'), 'cell_ontology_data_version': Value('string'), 'cell_ontology_release': Value('string'), 'cell_ontology_sha256': Value('string'), 'cell_ontology_source_url': Value('string'), 'context_dependence': {'note': Value('string'), 'relations': List({'child_context_id': Value('string'), 'direct': Value('bool'), 'parent_context_id': Value('string'), 'shared_donor_count': Value('int64')})}, 'contexts': List({'ancestor_context_ids': List(Value('string')), 'assay_capable_donors': {'any_specific_classification': Value('int64'), 'chromatin_accessibility': Value('int64'), 'ctcf_classification': Value('int64'), 'enhancer_classification': Value('int64'), 'full_classification_panel': Value('int64'), 'promoter_classification': Value('int64')}, 'context_id': Value('string'), 'descendant_context_ids': List(Value('string')), 'direct_child_context_ids': List(Value('string')), 'direct_parent_context_ids': List(Value('string')), 'donor_count': Value('int64'), 'is_nested_context': Value('bool'), 'is_summary_parent': Value('bool'), 'life_stages': List(Value('string')), 'lineages': List(Value('string')), 'member_profile_indices': List(Value('int64')), 'ontology_id': Value('string'), 'ontology_name': Value('string'), 'ontology_release_name': 
...
'WARNING: low read depth': Value('int64'), 'WARNING: low read length': Value('int64'), 'WARNING: low spot score': Value('int64'), 'WARNING: matching md5 sums': Value('int64'), 'WARNING: mild to moderate bottlenecking': Value('int64'), 'WARNING: missing footprints': Value('int64'), 'WARNING: mixed read lengths': Value('int64'), 'WARNING: moderate library complexity': Value('int64')}, 'policy': Value('string'), 'source_counts': {'NOT_COMPLIANT: control insufficient read depth': Value('int64'), 'NOT_COMPLIANT: insufficient read depth': Value('int64'), 'NOT_COMPLIANT: insufficient read length': Value('int64'), 'NOT_COMPLIANT: unreplicated experiment': Value('int64'), 'WARNING: antibody characterized with exemption': Value('int64'), 'WARNING: borderline replicate concordance': Value('int64'), 'WARNING: control low read depth': Value('int64'), 'WARNING: inconsistent control read length': Value('int64'), 'WARNING: inconsistent control run_type': Value('int64'), 'WARNING: inconsistent platforms': Value('int64'), 'WARNING: low read depth': Value('int64'), 'WARNING: low read length': Value('int64'), 'WARNING: low spot score': Value('int64'), 'WARNING: matching md5 sums': Value('int64'), 'WARNING: mild to moderate bottlenecking': Value('int64'), 'WARNING: missing controlled_by': Value('int64'), 'WARNING: missing footprints': Value('int64'), 'WARNING: mixed read lengths': Value('int64'), 'WARNING: mixed run types': Value('int64'), 'WARNING: moderate library complexity': Value('int64')}}}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              assembly: string
              catalog: struct<path: string, sha256: string, size: int64>
                child 0, path: string
                child 1, sha256: string
                child 2, size: int64
              ccre_count: int64
              class_codes: struct<0: struct<description: string, label: string>, 1: struct<description: string, label: string>, (... 329 chars omitted)
                child 0, 0: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 1, 1: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 2, 2: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 3, 3: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 4, 4: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 5, 5: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 6, 6: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 7, 7: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
                child 8, 8: struct<description: string, label: string>
                    child 0, description: string
                    child 1, label: string
              created_at: timestamp[s]
              immune_matrix: struct<layout: string, path: string, sha256: string, shape: list<i
              ...
              chars omitted)
                child 0, immune_biosamples: struct<call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, d (... 132 chars omitted)
                    child 0, call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, dELS: int64, inactive (... 21 chars omitted)
                        child 0, CA: int64
                        child 1, CA-CTCF: int64
                        child 2, CA-H3K4me3: int64
                        child 3, CA-TF: int64
                        child 4, PLS: int64
                        child 5, dELS: int64
                        child 6, inactive: int64
                        child 7, pELS: int64
                    child 1, observed_labels: list<item: string>
                        child 0, item: string
                    child 2, supported_but_unobserved_labels: list<item: string>
                        child 0, item: string
                child 1, tissues: struct<call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, d (... 132 chars omitted)
                    child 0, call_counts: struct<CA: int64, CA-CTCF: int64, CA-H3K4me3: int64, CA-TF: int64, PLS: int64, dELS: int64, inactive (... 21 chars omitted)
                        child 0, CA: int64
                        child 1, CA-CTCF: int64
                        child 2, CA-H3K4me3: int64
                        child 3, CA-TF: int64
                        child 4, PLS: int64
                        child 5, dELS: int64
                        child 6, inactive: int64
                        child 7, pELS: int64
                    child 1, observed_labels: list<item: string>
                        child 0, item: string
                    child 2, supported_but_unobserved_labels: list<item: string>
                        child 0, item: string
              to
              {'artifacts': {'database': {'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}, 'members_tsv': {'path': Value('string'), 'sha256': Value('string'), 'size': Value('int64')}}, 'assembly': Value('string'), 'audit_policy_sha256': Value('string'), 'cell_ontology_data_version': Value('string'), 'cell_ontology_release': Value('string'), 'cell_ontology_sha256': Value('string'), 'cell_ontology_source_url': Value('string'), 'context_dependence': {'note': Value('string'), 'relations': List({'child_context_id': Value('string'), 'direct': Value('bool'), 'parent_context_id': Value('string'), 'shared_donor_count': Value('int64')})}, 'contexts': List({'ancestor_context_ids': List(Value('string')), 'assay_capable_donors': {'any_specific_classification': Value('int64'), 'chromatin_accessibility': Value('int64'), 'ctcf_classification': Value('int64'), 'enhancer_classification': Value('int64'), 'full_classification_panel': Value('int64'), 'promoter_classification': Value('int64')}, 'context_id': Value('string'), 'descendant_context_ids': List(Value('string')), 'direct_child_context_ids': List(Value('string')), 'direct_parent_context_ids': List(Value('string')), 'donor_count': Value('int64'), 'is_nested_context': Value('bool'), 'is_summary_parent': Value('bool'), 'life_stages': List(Value('string')), 'lineages': List(Value('string')), 'member_profile_indices': List(Value('int64')), 'ontology_id': Value('string'), 'ontology_name': Value('string'), 'ontology_release_name': 
              ...
              'WARNING: low read depth': Value('int64'), 'WARNING: low read length': Value('int64'), 'WARNING: low spot score': Value('int64'), 'WARNING: matching md5 sums': Value('int64'), 'WARNING: mild to moderate bottlenecking': Value('int64'), 'WARNING: missing footprints': Value('int64'), 'WARNING: mixed read lengths': Value('int64'), 'WARNING: moderate library complexity': Value('int64')}, 'policy': Value('string'), 'source_counts': {'NOT_COMPLIANT: control insufficient read depth': Value('int64'), 'NOT_COMPLIANT: insufficient read depth': Value('int64'), 'NOT_COMPLIANT: insufficient read length': Value('int64'), 'NOT_COMPLIANT: unreplicated experiment': Value('int64'), 'WARNING: antibody characterized with exemption': Value('int64'), 'WARNING: borderline replicate concordance': Value('int64'), 'WARNING: control low read depth': Value('int64'), 'WARNING: inconsistent control read length': Value('int64'), 'WARNING: inconsistent control run_type': Value('int64'), 'WARNING: inconsistent platforms': Value('int64'), 'WARNING: low read depth': Value('int64'), 'WARNING: low read length': Value('int64'), 'WARNING: low spot score': Value('int64'), 'WARNING: matching md5 sums': Value('int64'), 'WARNING: mild to moderate bottlenecking': Value('int64'), 'WARNING: missing controlled_by': Value('int64'), 'WARNING: missing footprints': Value('int64'), 'WARNING: mixed read lengths': Value('int64'), 'WARNING: mixed run types': Value('int64'), 'WARNING: moderate library complexity': Value('int64')}}}
              because column names don't match

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SCREEN Registry V4 — prepared tissue and immune-cell cCRE contexts (GRCh38)

A prepared, categorical view of ENCODE SCREEN Registry V4 candidate cis-regulatory elements (cCREs): per-cCRE classification across 38 organ/tissue aggregates (cancer cell lines excluded) and 28 curated baseline immune/hematopoietic cell contexts (Cell-Ontology-grounded, donor-aware, ENCODE-audit-filtered). Built for interactive variant review — one unsigned byte per cCRE/biosample; assay Z-scores are deliberately not retained.

This bundle spares each user roughly 32 GB of source downloads and hours of processing (ENCODE metadata enrichment, matrix encoding, ontology curation). It is the exact output of the reproducible build pipeline in the WES/WGS diagnostic analysis pipeline (IEI variant-review workbench); the same software validates this bundle's internal checksums on installation.

Files

File Contents
screen.registry-v4.catalog.sqlite3 cCRE catalog (accessions, classes, coordinates; BED 0-based half-open)
screen.registry-v4.tissues.u8 tissue-aggregate class matrix (uint8 per cCRE × 38 aggregates)
screen.registry-v4.immune.u8 immune biosample class matrix (uint8 per cCRE × donor-level profiles)
screen.registry-v4.immune-contexts.sqlite3 curated context definitions and membership
screen.registry-v4.immune-context-members.tsv human-readable context membership
screen.registry-v4.immune-contexts.json manifest: provenance, per-file SHA-256, counts, curation policy identity
screen.registry-v4.prepared.json matrix preparation manifest

Provenance (pinned and recorded in the manifests)

  • Source: ENCODE SCREEN Registry V4, GRCh38 (https://screen.wenglab.org/, downloads.wenglab.org) and the ENCODE portal metadata API (https://www.encodeproject.org/).
  • Cell Ontology: release v2026-06-08, SHA-256 73996c63…e869f8c1c (pinned).
  • ENCODE audit policy: SHA-256 83b11c93…a38c09c (pinned; experiments failing the policy are excluded, tolerated warnings are recorded).
  • Immune curation: 166 baseline donor-representative profiles across 97 distinct donors; one categorical vote per donor per context; nested Cell Ontology contexts record shared-donor dependence rather than being presented as independent evidence.
  • Per-file SHA-256 checksums are inside screen.registry-v4.immune-contexts.json.

Interpretation boundaries

  • Tissue aggregates and immune contexts are observed evidence, not target-gene assignments — cCRE positional overlap is not by itself pathogenicity evidence, and the nearest gene is not necessarily regulated by the element.
  • A missing classification assay is unavailable evidence, never a negative result; partial classifications are labeled as such.
  • "Not detected" means not detected in the represented SCREEN profiles, not universally inactive.

License and attribution

  • ENCODE data: distributed under the ENCODE Data Use Policy — "External data users may freely download, analyze and publish results based on any ENCODE data without restrictions." Please cite the ENCODE Consortium and SCREEN: The ENCODE Project Consortium et al., Expanded encyclopaedias of DNA elements in the human and mouse genomes, Nature 583, 699–710 (2020).
  • Cell Ontology: CC-BY 4.0 — https://github.com/obophenotype/cell-ontology.
  • This prepared compilation is shared under CC-BY 4.0.

Use with the IEI variant-review workbench

In the workbench: Regulatory evidence → Use prepared bundle, selecting the folder containing these files (or the screen.registry-v4.immune-contexts.json manifest). The workbench validates the manifest checksums and stores only a local pointer; the matrices stay where you put them.
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Total file size:
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