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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 20 new columns ({'Gene count', 'Folds/repeats', 'Query count', 'Metacell count', 'Target count', 'Split/evaluation design', 'Selection criteria', 'Public URL/DOI', 'Record type', 'Training cell count', 'Analysis', 'Dataset/cohort ID', 'Tissue/cell line', 'Role', 'Class/context count', 'Source cell count', 'Accession', 'Species', 'Test cell count', 'Pair count'}) and 3 missing columns ({'cell_id', 'label', 'study'}).
This happened while the csv dataset builder was generating data using
hf://datasets/netbiolab/MetacellFormer-evaluation/contracts/evaluation_roster.tsv (at revision 03a8edfda42690bfa38f34f0a71c8967bd675584), ['hf://datasets/netbiolab/MetacellFormer-evaluation@03a8edfda42690bfa38f34f0a71c8967bd675584/contracts/pc9/test_cells.tsv.gz', 'hf://datasets/netbiolab/MetacellFormer-evaluation@03a8edfda42690bfa38f34f0a71c8967bd675584/contracts/evaluation_roster.tsv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 784, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._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
Analysis: string
Dataset/cohort ID: string
Record type: string
Accession: string
Public URL/DOI: string
Species: string
Tissue/cell line: string
Role: string
Split/evaluation design: string
Source cell count: double
Training cell count: double
Test cell count: double
Metacell count: double
Target count: double
Gene count: double
Class/context count: double
Query count: double
Pair count: double
Folds/repeats: string
Selection criteria: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2822
to
{'cell_id': Value('string'), 'study': Value('string'), 'label': Value('int64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 20 new columns ({'Gene count', 'Folds/repeats', 'Query count', 'Metacell count', 'Target count', 'Split/evaluation design', 'Selection criteria', 'Public URL/DOI', 'Record type', 'Training cell count', 'Analysis', 'Dataset/cohort ID', 'Tissue/cell line', 'Role', 'Class/context count', 'Source cell count', 'Accession', 'Species', 'Test cell count', 'Pair count'}) and 3 missing columns ({'cell_id', 'label', 'study'}).
This happened while the csv dataset builder was generating data using
hf://datasets/netbiolab/MetacellFormer-evaluation/contracts/evaluation_roster.tsv (at revision 03a8edfda42690bfa38f34f0a71c8967bd675584), ['hf://datasets/netbiolab/MetacellFormer-evaluation@03a8edfda42690bfa38f34f0a71c8967bd675584/contracts/pc9/test_cells.tsv.gz', 'hf://datasets/netbiolab/MetacellFormer-evaluation@03a8edfda42690bfa38f34f0a71c8967bd675584/contracts/evaluation_roster.tsv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
cell_id string | study string | label int64 |
|---|---|---|
Data11::GSM4494347_GTTTGCTGTTTC | GSE149214 | 0 |
Data11::GSM4494347_AGCAAATCACCG | GSE149214 | 0 |
Data11::GSM4494347_CATGCCTGGTGT | GSE149214 | 0 |
Data11::GSM4494347_CTTTAACCGCCT | GSE149214 | 0 |
Data11::GSM4494347_CACCCCCAAGCA | GSE149214 | 0 |
Data11::GSM4494347_CCCGCCACCCAG | GSE149214 | 0 |
Data11::GSM4494347_ACAGGAGACTAT | GSE149214 | 0 |
Data11::GSM4494347_AACGTCTATAAT | GSE149214 | 0 |
Data11::GSM4494347_TATCGAGTTCAA | GSE149214 | 0 |
Data11::GSM4494347_GACGCCGGCACT | GSE149214 | 0 |
Data11::GSM4494347_TTTCGCGGACCN | GSE149214 | 0 |
Data11::GSM4494347_CCATACAAGTTG | GSE149214 | 0 |
Data11::GSM4494347_GATCGCCAACTA | GSE149214 | 0 |
Data11::GSM4494347_GCTCCTTTTTTC | GSE149214 | 0 |
Data11::GSM4494347_CGCCCCCCTTGT | GSE149214 | 0 |
Data11::GSM4494347_AATGTGACCAGC | GSE149214 | 0 |
Data11::GSM4494347_CGGTAGAATTTA | GSE149214 | 0 |
Data11::GSM4494347_TGGCCAACTTTT | GSE149214 | 0 |
Data11::GSM4494347_GCATTACTGCCN | GSE149214 | 0 |
Data11::GSM4494347_CGTCCCCAACGC | GSE149214 | 0 |
Data11::GSM4494347_AAAATTGGGCTG | GSE149214 | 0 |
Data11::GSM4494347_TCAATTTCACGG | GSE149214 | 0 |
Data11::GSM4494347_CTACAGACGCCT | GSE149214 | 0 |
Data11::GSM4494347_TTGAAGCGACCA | GSE149214 | 0 |
Data11::GSM4494347_TTGCGAGCCTAT | GSE149214 | 0 |
Data11::GSM4494347_ATTGGTTCACAA | GSE149214 | 0 |
Data11::GSM4494347_ACAGAACATGTA | GSE149214 | 0 |
Data11::GSM4494347_CCGGCCAATCGA | GSE149214 | 0 |
Data11::GSM4494347_GGTTTTGCCCAC | GSE149214 | 0 |
Data11::GSM4494347_TTACACAATAAN | GSE149214 | 0 |
Data11::GSM4494347_GTCACGAACTCA | GSE149214 | 0 |
Data11::GSM4494347_CGAGCCCCCTTT | GSE149214 | 0 |
Data11::GSM4494347_GTTTAAGGTATA | GSE149214 | 0 |
Data11::GSM4494347_ACCTCGCGAAGG | GSE149214 | 0 |
Data11::GSM4494347_GAGCCATGTTTT | GSE149214 | 0 |
Data11::GSM4494347_GACACCCGAAAA | GSE149214 | 0 |
Data11::GSM4494347_GCACGAAAGCAG | GSE149214 | 0 |
Data11::GSM4494347_GGACCCCACAGC | GSE149214 | 0 |
Data11::GSM4494347_CAAAACTTGTGA | GSE149214 | 0 |
Data11::GSM4494347_TACTAAACTGGC | GSE149214 | 0 |
Data11::GSM4494347_ACCTTTCCACCA | GSE149214 | 0 |
Data11::GSM4494347_CACTTTAACCTT | GSE149214 | 0 |
Data11::GSM4494347_ACTTAACAAATC | GSE149214 | 0 |
Data11::GSM4494347_GTGCGTAACATC | GSE149214 | 0 |
Data11::GSM4494347_AAGGATCTATTA | GSE149214 | 0 |
Data11::GSM4494347_AACGACGCTTTN | GSE149214 | 0 |
Data11::GSM4494347_CTGATTGCTTGT | GSE149214 | 0 |
Data11::GSM4494347_TCGTCTGATCTC | GSE149214 | 0 |
Data11::GSM4494347_CAACCGTTATAA | GSE149214 | 0 |
Data11::GSM4494347_TACTACAGCTTA | GSE149214 | 0 |
Data11::GSM4494347_GGTAACACTATG | GSE149214 | 0 |
Data11::GSM4494347_CGGCATCTTCTT | GSE149214 | 0 |
Data11::GSM4494347_CTCATAAGTTTT | GSE149214 | 0 |
Data11::GSM4494347_CTCGCCCATTAN | GSE149214 | 0 |
Data11::GSM4494347_CTGCTTCAGTGC | GSE149214 | 0 |
Data11::GSM4494347_CCGAAAGCCATT | GSE149214 | 0 |
Data11::GSM4494347_GTTGGATTTGTN | GSE149214 | 0 |
Data11::GSM4494347_AGCTTGGACTCA | GSE149214 | 0 |
Data11::GSM4494347_ATGTTAGTGTCT | GSE149214 | 0 |
Data11::GSM4494347_AATCAATTGCCG | GSE149214 | 0 |
Data11::GSM4494347_TTACTAAGTAAC | GSE149214 | 0 |
Data11::GSM4494347_CGACGCCCCCGG | GSE149214 | 0 |
Data11::GSM4494347_GCGGAGCAGCGC | GSE149214 | 0 |
Data11::GSM4494347_CGAAAGACCGCA | GSE149214 | 0 |
Data11::GSM4494347_TACCGAACTTCT | GSE149214 | 0 |
Data11::GSM4494347_TAGACTTTCGTN | GSE149214 | 0 |
Data11::GSM4494347_GGCTAACACGAG | GSE149214 | 0 |
Data11::GSM4494347_GGAGCCCAACTG | GSE149214 | 0 |
Data11::GSM4494347_TAAAGCTCCAAT | GSE149214 | 0 |
Data11::GSM4494347_TTATAACCCGTG | GSE149214 | 0 |
Data11::GSM4494347_AGGCTTGGCTCG | GSE149214 | 0 |
Data11::GSM4494347_TCAATTCCTCCC | GSE149214 | 0 |
Data11::GSM4494347_ACCCGGGGAAGT | GSE149214 | 0 |
Data11::GSM4494347_GTACAACTCACG | GSE149214 | 0 |
Data11::GSM4494347_TCGATGATCTGC | GSE149214 | 0 |
Data11::GSM4494347_TTACGACCAGTT | GSE149214 | 0 |
Data11::GSM4494347_GTTTCTGCAATA | GSE149214 | 0 |
Data11::GSM4494347_GGTTATCATCCT | GSE149214 | 0 |
Data11::GSM4494347_GGAGAGCGACTG | GSE149214 | 0 |
Data11::GSM4494347_GCATGATCTCAT | GSE149214 | 0 |
Data11::GSM4494347_GTTCAGCCAAAA | GSE149214 | 0 |
Data11::GSM4494347_AGGCGCCTTTAT | GSE149214 | 0 |
Data11::GSM4494347_TATAGAACACGG | GSE149214 | 0 |
Data11::GSM4494347_AGATTATCCTAT | GSE149214 | 0 |
Data11::GSM4494347_AATCATAAATTA | GSE149214 | 0 |
Data11::GSM4494347_ATCATCGTAAAC | GSE149214 | 0 |
Data11::GSM4494347_GTATTTTCTCAA | GSE149214 | 0 |
Data11::GSM4494347_TCTATCTCAGAA | GSE149214 | 0 |
Data11::GSM4494347_ACACTAATACCC | GSE149214 | 0 |
Data11::GSM4494347_ATACTTGTATCT | GSE149214 | 0 |
Data11::GSM4494347_CGTGCTCGCTCT | GSE149214 | 0 |
Data11::GSM4494347_CTAAGAGAAAGN | GSE149214 | 0 |
Data11::GSM4494347_TATACCACCAGT | GSE149214 | 0 |
Data11::GSM4494347_GGCTGCAGGCAA | GSE149214 | 0 |
Data11::GSM4494347_GTCGGGGCGTGT | GSE149214 | 0 |
Data11::GSM4494347_CAGATAAGTCTG | GSE149214 | 0 |
Data11::GSM4494347_TGGCCTGTTTCC | GSE149214 | 0 |
Data11::GSM4494347_TGATATGCCAGG | GSE149214 | 0 |
Data11::GSM4494347_ATAGGTATTCTC | GSE149214 | 0 |
Data11::GSM4494347_GATTTTGAGTTA | GSE149214 | 0 |
End of preview.
MetacellFormer evaluation inputs
This repository provides available input matrices, fixed cell rosters, labels, data splits and evaluation settings for the six main MetacellFormer benchmarks and the additional Gaussian-noise and cross-study PC9 analyses. Some source datasets must be obtained from their original providers, as described below. Published scores and predictions are provided separately in the article’s Figure Source Data and Supplementary Tables.
Layout
| Path | Purpose |
|---|---|
inputs/cell_annotation/ |
Seven archived cell-annotation matrices |
inputs/perturbation/K562.h5ad |
Fixed K562 input for exact and functional perturbation retrieval |
inputs/pc9/ |
Three external PC9 study matrices |
contracts/cell_type_annotation/ |
Nine rosters, metric labels, Gaussian protocol |
contracts/drug_response_classification/ |
Cell metadata and fixed folds |
contracts/perturbation_retrieval/ |
K562 selected cells and functional annotations |
contracts/pc9/ |
Training/test cell IDs, comparison membership and metadata, gene mapping, protocol |
contracts/tissue_specificity_prediction/ |
GTEx labels, folds and shared gene support |
contracts/protein_interaction_prediction/ |
HuRI pairs, folds and gene-info snapshot |
contracts/evaluation_roster.tsv |
Cohort and evaluation design for the retained analyses |
contracts/model_representations.tsv |
Model dimensions, pooling and gene-mapping settings |
input_manifest.tsv |
Included and externally obtained inputs, source terms, checksums and preparation notes |
The six main benchmarks are cell-type annotation, drug-response classification, exact perturbation-state retrieval, functional perturbation retrieval, tissue-specificity prediction, and protein-interaction prediction. MetacellFormer-SC is the matched control. Gaussian and PC9 analyses are additional evaluations.
Input preparation
- Cell-annotation matrices retain their archived numerical values and feature order.
obs.splituses the original0training and2test codes.var.metacellformer_gene_idandvar.geneformer_ensembl_idretain model-specific feature mappings; do not collapse MetacellFormer aliases before Gaussian preparation. MCA and MHSP use the historical human one-to-one ortholog axes. - K562 preserves the fixed 262,998-cell selected population and 8,563-gene axis. Align embeddings with
contracts/perturbation_retrieval/selected_cells.tsv; functional groups are infunctional_annotations.tsv. - PC9 study inputs must be encoded separately and aligned to
contracts/pc9/test_cells.tsv.gz. GSE282074 retains decimal RSEM expected counts; its controls are shared by two comparison memberships. The 2,393 training cells require authorized scDrugMap Data11 access. - HumanPBMC, Pancrm and the exact processed scDrugMap matrices are not redistributed. Obtain them from the sources in
input_manifest.tsvand align to the released rosters, IDs and folds. GTEx and HuRI use released labels/pairs and fixed folds with gene embeddings
The companion GitHub repository documents embedding extraction and scoring in benchmarks/README.md.
Verify a download from this directory with sha256sum -c checksums.sha256.
Terms
Derived evaluation contracts are CC BY 4.0 where applicable. Input matrices and reference files retain their upstream terms; consult input_manifest.tsv and LICENSES.md. This repository does not relicense upstream inputs.
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