Open SMA Research Data
Collection
6 items • Updated
Datasets:
Modalities:
Text
Languages:
English
Size:
n<1K
Tags:
spinal-muscular-atrophy
rna-seq
transcriptomics
motor-neurons
induced-pluripotent-stem-cells
ai4science
License:
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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 46 new columns ({'avgLength', 'ReadHash', 'spots', 'size_MB', 'download_path', 'g1k_pop_code', 'Disease', 'Platform', 'Sex', 'ReleaseDate', 'TaxID', 'Model', 'Subject_ID', 'Study_Pubmed_id', 'Experiment', 'CenterName', 'SampleType', 'Body_Site', 'LibraryLayout', 'ScientificName', 'Consent', 'LibraryName', 'Affection_Status', 'BioSample', 'Analyte_Type', 'Sample', 'BioProject', 'Run', 'RunHash', 'dbgap_study_accession', 'SampleName', 'SRAStudy', 'Submission', 'LibraryStrategy', 'spots_with_mates', 'bases', 'Histological_Type', 'ProjectID', 'Tumor', 'LibrarySource', 'InsertDev', 'g1k_analysis_group', 'LoadDate', 'InsertSize', 'AssemblyName', 'LibrarySelection'}) and 7 missing columns ({'sha256', 'terms', 'description', 'size_bytes', 'source_id', 'upstream_filename', 'repository_path'}).
This happened while the csv dataset builder was generating data using
hf://datasets/YannisTevissen/sma-gse108094-motor-neuron-rnaseq/mirror/SRP126773_runinfo.csv (at revision f40512d502202d407418dab6cd59003671ad89d5), ['hf://datasets/YannisTevissen/sma-gse108094-motor-neuron-rnaseq@f40512d502202d407418dab6cd59003671ad89d5/mirror/MANIFEST.csv', 'hf://datasets/YannisTevissen/sma-gse108094-motor-neuron-rnaseq@f40512d502202d407418dab6cd59003671ad89d5/mirror/SRP126773_runinfo.csv']
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 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, 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 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
Run: string
ReleaseDate: string
LoadDate: string
spots: int64
bases: int64
spots_with_mates: int64
avgLength: int64
size_MB: int64
AssemblyName: double
download_path: string
Experiment: string
LibraryName: double
LibraryStrategy: string
LibrarySelection: string
LibrarySource: string
LibraryLayout: string
InsertSize: int64
InsertDev: int64
Platform: string
Model: string
SRAStudy: string
BioProject: string
Study_Pubmed_id: int64
ProjectID: int64
Sample: string
BioSample: string
SampleType: string
TaxID: int64
ScientificName: string
SampleName: string
g1k_pop_code: double
source: double
g1k_analysis_group: double
Subject_ID: double
Sex: double
Disease: double
Tumor: string
Affection_Status: double
Analyte_Type: double
Histological_Type: double
Body_Site: double
CenterName: string
Submission: string
dbgap_study_accession: double
Consent: string
RunHash: string
ReadHash: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 5906
to
{'source': Value('string'), 'source_id': Value('string'), 'upstream_filename': Value('string'), 'repository_path': Value('string'), 'size_bytes': Value('int64'), 'sha256': Value('string'), 'terms': Value('string'), 'description': Value('string')}
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 1683, 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 1839, 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 46 new columns ({'avgLength', 'ReadHash', 'spots', 'size_MB', 'download_path', 'g1k_pop_code', 'Disease', 'Platform', 'Sex', 'ReleaseDate', 'TaxID', 'Model', 'Subject_ID', 'Study_Pubmed_id', 'Experiment', 'CenterName', 'SampleType', 'Body_Site', 'LibraryLayout', 'ScientificName', 'Consent', 'LibraryName', 'Affection_Status', 'BioSample', 'Analyte_Type', 'Sample', 'BioProject', 'Run', 'RunHash', 'dbgap_study_accession', 'SampleName', 'SRAStudy', 'Submission', 'LibraryStrategy', 'spots_with_mates', 'bases', 'Histological_Type', 'ProjectID', 'Tumor', 'LibrarySource', 'InsertDev', 'g1k_analysis_group', 'LoadDate', 'InsertSize', 'AssemblyName', 'LibrarySelection'}) and 7 missing columns ({'sha256', 'terms', 'description', 'size_bytes', 'source_id', 'upstream_filename', 'repository_path'}).
This happened while the csv dataset builder was generating data using
hf://datasets/YannisTevissen/sma-gse108094-motor-neuron-rnaseq/mirror/SRP126773_runinfo.csv (at revision f40512d502202d407418dab6cd59003671ad89d5), ['hf://datasets/YannisTevissen/sma-gse108094-motor-neuron-rnaseq@f40512d502202d407418dab6cd59003671ad89d5/mirror/MANIFEST.csv', 'hf://datasets/YannisTevissen/sma-gse108094-motor-neuron-rnaseq@f40512d502202d407418dab6cd59003671ad89d5/mirror/SRP126773_runinfo.csv']
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.
source string | source_id string | upstream_filename string | repository_path string | size_bytes int64 | sha256 string | terms string | description string |
|---|---|---|---|---|---|---|---|
NCBI GEO | GEO:GSE108094 | GSE108094_gene_exp.diff.gz | mirror/GSE108094_gene_exp.diff.gz | 2,217,963 | f2c1872e0fff1d827f1558bd330aa7db22d6b30b4b2b672ece0a76667565edc6 | NCBI molecular-data terms | Differential expression output |
NCBI GEO | GEO:GSE108094 | GSE108094_SE.MATS.ReadsOnTargetAndJunctionCounts.txt.gz | mirror/GSE108094_SE.MATS.ReadsOnTargetAndJunctionCounts.txt.gz | 2,459,181 | 9f709932198bef2748885b1a95ef0f1c72f2a5b736e6af2056023774dc661459 | NCBI molecular-data terms | Alternative splicing output |
NCBI GEO | GEO:GSE108094 | GSE108094_series_matrix.txt.gz | mirror/GSE108094_series_matrix.txt.gz | 3,586 | a53900891667a7e9ef59b4593825b740408dac14ab9fe1fe8eda656a7b81a5e5 | NCBI molecular-data terms | Series matrix metadata |
NCBI GEO | GEO:GSE108094 | GSE108094_family.xml.tgz | mirror/GSE108094_family.xml.tgz | 4,189 | 2a106192b37d8a5b65589673574f181be71425539db9cd1d50080bcb471b8ab2 | NCBI molecular-data terms | MINiML family metadata |
NCBI GEO | GEO:GSE108094 | GSE108094_family.soft.gz | mirror/GSE108094_family.soft.gz | 3,743 | 5bafb5f169dc287fe494ac5b7aa874ddb0e900b914ad989494c0ad40025c9151 | NCBI molecular-data terms | SOFT family metadata |
NCBI SRA | SRA:SRP126773 | SRP126773_runinfo.csv | mirror/SRP126773_runinfo.csv | 4,240 | b4142636163c173ad727fc9c8900eefbf51d6ea5d7dad3c9d284c3a8ac11a9c8 | NCBI molecular-data terms | Complete inventory of eight raw runs; payload not included |
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GSE108094 SMA Motor-Neuron RNA-seq
This repository contains processed RNA-sequencing results and GEO/SRA metadata for human SMA and control iPSC-derived motor neurons.
The experiment has eight libraries from four biological cell lines: two SMA and two control lines, each with two sequencing replicates. The repository contains the differential-expression output, alternative-splicing output, series matrix, MINiML family file, SOFT family file, and SRA run inventory. The accompanying MANIFEST.csv records sizes, SHA-256 checksums, accessions, terms, and file descriptions.
The eight raw-read runs total 188,422 MB as reported by SRA—about 184 GiB—and are not included. SRP126773_runinfo.csv lists every run, sample, size, and NCBI download path.
Useful tasks
- reproduce differential-expression and alternative-splicing analyses;
- demonstrate accession-aware bioinformatics workflows;
- explore pathway-level signals with careful biological-replicate accounting.
Limitations
Eight libraries are not eight independent people. Splits must respect the underlying cell line and experimental design. This is a cellular disease model, not clinical evidence or a diagnostic dataset.
Source citation and attribution
Rizzo F, Nizzardo M, Vashisht S, et al. (2019). Key role of SMN/SYNCRIP and RNA-Motif 7 in spinal muscular atrophy: RNA-Seq and motif analysis of human motor neurons. Brain, 142(2), 276–294. https://doi.org/10.1093/brain/awy330
Cite GEO accession GSE108094, SRA study SRP126773, and the source publication. NCBI places no restrictions on use or distribution of its molecular data, but it cannot transfer rights it does not hold; downstream users remain responsible for any submitter rights.
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