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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 3 new columns ({'n_cells', 'target_gene', 'median_umi_per_cell'}) and 1 missing columns ({'SAMD11'}).
This happened while the csv dataset builder was generating data using
hf://datasets/cyrilzakka/arc-institute-virtual-cell-dataset/pert_counts_Validation.csv (at revision 952b34cd3b0698a9846e9d444938e0805e76df56)
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 "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 643, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
target_gene: string
n_cells: int64
median_umi_per_cell: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 632
to
{'SAMD11': Value(dtype='string', id=None)}
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 1431, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 992, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
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 3 new columns ({'n_cells', 'target_gene', 'median_umi_per_cell'}) and 1 missing columns ({'SAMD11'}).
This happened while the csv dataset builder was generating data using
hf://datasets/cyrilzakka/arc-institute-virtual-cell-dataset/pert_counts_Validation.csv (at revision 952b34cd3b0698a9846e9d444938e0805e76df56)
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.
SAMD11 string |
|---|
NOC2L |
KLHL17 |
PLEKHN1 |
PERM1 |
HES4 |
ISG15 |
AGRN |
RNF223 |
C1orf159 |
TTLL10 |
TNFRSF18 |
TNFRSF4 |
SDF4 |
B3GALT6 |
C1QTNF12 |
UBE2J2 |
SCNN1D |
ACAP3 |
PUSL1 |
INTS11 |
CPTP |
TAS1R3 |
DVL1 |
MXRA8 |
AURKAIP1 |
CCNL2 |
ANKRD65 |
TMEM88B |
VWA1 |
ATAD3C |
ATAD3B |
ATAD3A |
TMEM240 |
SSU72 |
FNDC10 |
MIB2 |
MMP23B |
CDK11B |
CDK11A |
NADK |
GNB1 |
CALML6 |
TMEM52 |
CFAP74 |
GABRD |
PRKCZ |
FAAP20 |
SKI |
RER1 |
PEX10 |
PLCH2 |
PANK4 |
HES5 |
TNFRSF14 |
PRXL2B |
MMEL1 |
ACTRT2 |
PRDM16 |
ARHGEF16 |
MEGF6 |
TPRG1L |
WRAP73 |
TP73 |
CCDC27 |
SMIM1 |
LRRC47 |
CEP104 |
DFFB |
C1orf174 |
AJAP1 |
NPHP4 |
KCNAB2 |
CHD5 |
RNF207 |
ICMT |
HES3 |
GPR153 |
ACOT7 |
HES2 |
ESPN |
TNFRSF25 |
PLEKHG5 |
NOL9 |
TAS1R1 |
ZBTB48 |
KLHL21 |
PHF13 |
THAP3 |
DNAJC11 |
CAMTA1 |
VAMP3 |
PER3 |
UTS2 |
TNFRSF9 |
ERRFI1 |
SLC45A1 |
RERE |
ENO1 |
CA6 |
SLC2A7 |
End of preview.
ARC Institute Virtual Cell Challenge
Please check out the official website for the challenge rules and deadlines.
About
For this challenge, single-cell functional genomics was used to generate approximately 300,000 single-cell RNA-seq profiles by silencing 300 carefully selected genes using CRISPR interference (CRISPRi). 10x Genomics GEM-X Flex and Illumina sequencing were used to obtain single-cell gene expression profiles. The data are split into three groups for the Virtual Cell Challenge, to allow for training, validation of initial results, and developing a final entry for the competition.
- Training set consisting of single-cell profiles for 150 gene perturbations (~150,000 cells)
- Validation set of 50 gene perturbations, for which entrants’ predicted transcriptomic results will be used to create a live ranking leaderboard during the challenge
Training data [15GB]
Gene Expression File in AnnData H5AD format.
Obs
| cell barcode-batch index | target_gene | guide_id | batch |
|---|---|---|---|
| AAACAAGCAACCTTGTACTTTAGG-Flex_1_01 | CHMP3 | CHMP3_P1P2_A|CHMP3_P1P2_B | Flex_1_01 |
| TTTGGACGTGGTGCAGATTCGGTT-Flex_3_16 | non-targeting | non-targeting_00035|non-targeting_03439 | Flex_3_16 |
Var — index of gene names to predict adfile.var.index
Index(['SAMD11', 'NOC2L', 'KLHL17', 'PLEKHN1', 'PERM1', 'HES4', 'ISG15', 'AGRN', 'RNF223', 'C1orf159', ... 'MT-ND5', 'MT-ND6', 'MT-CYB'], dtype='object', length=18080)
Control Cells There are 38,176 unperturbed control cells in the training data denoted with a target_gene value of ‘non-targeting’. Competitors can optionally predict expression values for the control set during submission or copy expression values over from the training set.
Validation data [1kb]
| Field name | Description |
|---|---|
| target_gene | Gene symbol targeted for perturbation |
| n_cells | Recommended number of cells to predict for each perturbation to maximize model performance |
| median_umi_per_cell | The median number of Unique Molecular Identifiers per cell for each perturbation |
| target_gene | n_cells | median_umi_per_cell |
|---|---|---|
| SH3BP4 | 2925 | 54551.0 |
| ZNF581 | 2502 | 53803.5 |
| ANXA6 | 2496 | 55175.0 |
| PACSIN3 | 2101 | 54088.0 |
| MGST1 | 2096 | 54217.5 |
| IGF1R | 2056 | 53993.0 |
| ITGAV | 2034 | 55356.0 |
| SLIRP | 2000 | 54438.5 |
| CTSV | 1989 | 53173.0 |
| MTFR1 | 1787 | 53795.0 |
| ... | ... | ... |
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