manifest_version string | n_datasets int64 | datasets list |
|---|---|---|
1.0.0 | 18 | [
{
"name": "bladder_gouin",
"filename": "bladder_gouin.h5ad",
"size_bytes": 1748985672,
"n_cells": 67988,
"n_genes": 33538,
"cell_type_col": "celltype",
"n_cell_types": 5,
"accession": "GSE169379",
"disease": "urothelial_carcinoma",
"tissue": "bladder",
"platform": "snRNA-... |
ConvergeCELL Source Datasets — v1.0.0
Cached H5ADs of every single-cell RNA-seq dataset registered in the ConvergeCELL data catalog. Mirrors the original sources (GEO, figshare, Tabula Sapiens, CellxGene) so downstream code has a single, fast, versioned endpoint to fetch from.
Each row of every h5ad is one cell; each column is one gene (HGNC symbol). The exact obs/var schema follows whatever the original source provided — this bundle does not re-annotate, harmonize, or QC. For a harmonized, pseudobulked variant see converge-bio/pseudobulk-panel-v1.
Datasets (18)
| Name | Tissue | Disease | # Cells | # Cell Types | Accession | Publication |
|---|---|---|---|---|---|---|
bladder_gouin |
bladder | urothelial_carcinoma | 67,988 | 5 | GSE169379 | Gouin et al., Nature Communications 2021 |
bladder_gouin_normal |
bladder | healthy | 25,102 | — | GSE169379 | Gouin et al., Nature Communications 2021 |
bladder_lai |
bladder | urothelial_carcinoma | 36,788 | — | GSE135337 | Lai et al., Int J Cancer 2021 |
melanoma_jerby_arnon |
skin | melanoma | 7,186 | — | GSE115978 | Jerby-Arnon et al., Cell 2018 |
melanoma_sade_feldman |
skin | melanoma | 16,291 | — | GSE120575 | Sade-Feldman et al., Cell 2018 |
melanoma_tirosh |
skin | melanoma | 4,645 | 7 | GSE72056 | Tirosh et al., Science 2016 |
pbmc3k |
blood | healthy | 2,700 | — | N/A | 10X Genomics |
skin_healthy |
skin | healthy | 50,000 | 127 | CellxGene | CellxGene |
ts_blood |
blood | healthy | 10,000 | 107 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_bone_marrow |
bone_marrow | healthy | 10,000 | 119 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_eye |
eye | healthy | 10,000 | 105 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_heart |
heart | healthy | 10,000 | 67 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_kidney |
kidney | healthy | 10,000 | 114 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_liver |
liver | healthy | 10,000 | 117 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_lung |
lung | healthy | 10,000 | 167 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_pancreas |
islet | healthy | 10,000 | 54 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_skin |
skin | healthy | 10,000 | 105 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
ts_spleen |
spleen | healthy | 10,000 | 90 | figshare:14267219 | Tabula Sapiens Consortium, Science 2022 |
How to load
from huggingface_hub import hf_hub_download
import anndata as ad
path = hf_hub_download(
repo_id="nicolas-lynn/vcell-perturbation-source-data",
filename="ts_lung.h5ad", # any name from the table above
repo_type="dataset",
)
adata = ad.read_h5ad(path)
Or, programmatically via convergecell-data which will fall back to HF when the local cache is empty:
import convergecell_data as cd
adata = cd.load_dataset("ts_lung")
License
CC BY 4.0 for the manifest + dataset card. Each individual h5ad retains its upstream license — consult the publication column for the canonical source.
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