The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: ImportError
Message: To be able to use helical-ai/gastrulation_mmusculus, you need to install the following dependency: anndata.
Please install it using 'pip install anndata' for instance.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1914, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1880, in dataset_module_factory
return HubDatasetModuleFactoryWithScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1504, in get_module
local_imports = _download_additional_modules(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 354, in _download_additional_modules
raise ImportError(
ImportError: To be able to use helical-ai/gastrulation_mmusculus, you need to install the following dependency: anndata.
Please install it using 'pip install anndata' for instance.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.
Mouse Gastrulation scRNA-seq data
Across the animal kingdom, gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult organism.
Project information
Source: scRNA-seq whole mouse embryos during gastrulation and organoienesis, spanning days 6.5 to 8.5 of development, including embryonic and extraembryonic tissues.
Raw file:
Species
- Mus musculus (Mouse)
Assay details
- Assay: 10X Genomics Chromium system (version 1 chemistry)
- Number of Cells: 139,331
- Number of Genes: 29,452
Load the data
Load the dataset using Huggingface's optimized library and create the AnnData object:
from datasets import load_dataset
from scipy.sparse import lil_matrix
ds = load_dataset("helical-ai/gastrulation_mmusculus",trust_remote_code=True, split="train[:65%]",download_mode="reuse_cache_if_exists")
observation_columns = [obs for obs in list(ds.features.keys()) if not obs == 'raw_counts']
obs_data = pd.DataFrame(ds.select_columns(observation_columns).data.to_pandas(),columns=observation_columns)
lil = lil_matrix((len(ds),ds[0]['size']))
lil.data = np.array(ds['raw_counts'],dtype="object")
lil.rows = np.array(ds['rows'],dtype="object")
ann_data = ad.AnnData(lil.tocsr(),obs=obs_data)
ann_data.var_names = ds.features['raw_counts'].id.split(",")
Key metadata
| Category name | Types |
|---|---|
[1]stage |
E6.5, E6.75, E7.0, E7.25, E7.5, E7.75, E8.0, E8.25, E8.5, mixed_gastrulation |
[2]sequencing.batch |
1, 2, 3 |
[3]theiler |
TS10, TS11, TS12, TS9, TS9-10 |
celltype |
Allantois, Anterior Primitive Streak, Blood progenitors 1, Blood progenitors 2, Cardiomyocytes, Caudal Mesoderm, Caudal epiblast, Caudal neurectoderm, Def. endoderm, Endothelium, Epiblast, Erythroid1, Erythroid2, Erythroid3, ExE ectoderm, ExE endoderm, ExE mesoderm, Forebrain/Midbrain/Hindbrain, Gut, Haematoendothelial progenitors, Intermediate mesoderm, Mesenchyme, Mixed mesoderm, NMP, Nascent mesoderm, Neural crest, Notochord, PGC, Paraxial mesoderm, Parietal endoderm, Pharyngeal mesoderm, Primitive Streak, Rostral neurectoderm, Somitic mesoderm, Spinal cord, Surface ectoderm, Visceral endoderm, nan |
[1] Embryonic stages, specific days (E6.5–E8.5), and developmental phases in mouse embryogenesis.
[2] Different sequencing runs, crucial for managing technical variability in experiments.
[3] A staging system used in mouse embryology to describe specific morphological stages of development.
License information
Data was published in EMBL-EBI (Array Express), CC0.
This dataset was used in Pijuan-Sala et al, Nature 2019.
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