The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
comparison: string
U: double
p_value: double
n_high_medium: int64
n_low: int64
vs
compartment: string
n: int64
observed_mean_distance: double
null_mean: double
p_value: double
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 249, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4379, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2661, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2839, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2377, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 580, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
comparison: string
U: double
p_value: double
n_high_medium: int64
n_low: int64
vs
compartment: string
n: int64
observed_mean_distance: double
null_mean: double
p_value: doubleNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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ABCatlas — Data Repository
Comparative functional knowledgebase of ABC transporters in Homo sapiens (48 proteins) and Saccharomyces cerevisiae (31 proteins). Integrates six feature dimensions — subfamily classification, substrate specificity, subcellular localisation, structural similarity (TM-align), orthology confidence, and disease burden — into a single annotation framework.
Repository Structure
abcatlas_data/
├── raw/ Source data retrieved from public databases
└── processed/ Analysis outputs used in all figures and statistics
raw/
| File | Source | Description |
|---|---|---|
uniprot_human_abc.tsv |
UniProt | Human ABC transporter annotations (48 proteins) |
uniprot_yeast_abc.tsv |
UniProt | Yeast ABC transporter annotations (31 proteins) |
uniprot_human_domains.tsv |
UniProt | Domain architecture — human |
uniprot_yeast_domains.tsv |
UniProt | Domain architecture — yeast |
uniprot_human_go.tsv |
UniProt/GO | GO term assignments — human |
uniprot_yeast_go.tsv |
UniProt/GO | GO term assignments — yeast |
gtex_human_tissue_expression.tsv |
GTEx v8 | Median TPM across 54 human tissues |
hpa_localization.json |
Human Protein Atlas | Subcellular localisation — human |
clinvar_counts.tsv |
ClinVar | Pathogenic/likely-pathogenic variant counts per gene |
panther_human_yeast_orthologs.tsv |
PANTHER 18.0 | Human–yeast orthology assignments with confidence scores |
sgd_phenotypes.json |
SGD | Yeast phenotype and stress-response data |
alphafold_metadata.json |
AlphaFold DB v4 | Structure model metadata (pLDDT, coverage) |
processed/
| File | Description |
|---|---|
master_annotation_table.tsv |
Core table: 79 proteins x 48 columns, all feature dimensions merged |
master_gene_list.tsv |
Protein identifiers, gene names, organisms, and subfamily assignments |
feature_matrix.tsv |
Normalised feature vectors used as UMAP input |
landscape_coordinates.tsv |
UMAP embeddings and HDBSCAN cluster assignments (5 clusters) |
structural_similarity_tmscore_matrix.tsv |
All-versus-all TM-scores (3,081 pairs; 79 x 79) |
structural_comparison_ortholog_pairs.tsv |
TM-scores and structural metadata for confirmed ortholog pairs |
orthology_map.tsv |
Human–yeast ortholog pairs with PANTHER confidence tiers |
orthology_comparative_analysis.tsv |
Substrate Jaccard indices by orthology confidence group |
substrate_annotation.tsv |
Manually curated substrate class assignments |
localization_matrix.tsv |
Binary subcellular compartment matrix (HPA + SGD) |
expression_summary.tsv |
Tissue expression profiles — human (GTEx) |
disease_phenotype_summary.tsv |
OMIM disease associations and ClinVar variant counts |
variation_summary.tsv |
Variant burden summary per protein |
annotation_completeness_matrix.tsv |
Per-feature annotation completeness scores; flags one-sided gaps |
yeast_stress_response_summary.tsv |
Stress response rates across 13 conditions (SGD) |
structure_quality.tsv |
AlphaFold pLDDT scores and coverage per protein |
validation_mannwhitney_summary.tsv |
Mann–Whitney U test results for orthology–substrate analysis |
validation_permutation_summary.tsv |
Permutation test summary statistics |
validation_substrate_jaccard_groups.tsv |
Per-pair Jaccard scores used in validation |
Methods Summary
Dimensionality reduction: UMAP (n_neighbors=15, min_dist=0.1) on a six-dimension normalised feature matrix. Clustering: HDBSCAN (min_cluster_size=6). Structural comparisons: TM-align run on all 3,081 pairwise combinations of AlphaFold models. Orthology confidence tiers (High / Medium / Low) derived from PANTHER 18.0 scores. All analysis performed in Python 3.11 and R 4.5.
Citation
Harrzi Saad A. ABCatlas: a comparative functional knowledgebase of ABC transporters in Homo sapiens and Saccharomyces cerevisiae. 2026. Preprint / in review.
Licence
Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE for full terms.
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