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README.md

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+---
+license: cc-by-4.0
+task_categories:
+- feature-extraction
+tags:
+- single-cell
+- scRNA-seq
+- lung
+- biology
+- genomics
+pretty_name: Census Lung (single-cell RNA-seq, human lung)
+---
+
+# Census Lung
+
+A single-cell RNA-seq dataset of human lung tissue, assembled from the [CZ CELLxGENE Census](https://chanzuckerberg.github.io/cellxgene-census/) for use with [AUTOENCODIX](https://github.com/jan-forest/autoencodix_package) tutorials (`UsingPreTrainedModels.ipynb`, `Varix.ipynb`).
+
+## Contents
+
+- **89,030 cells × 8,189 genes**, filtered to the gene set used by the `Ontix-Dim24-Gemini3ProPreview` pretrained model (a chromosome/GO-ontology-informed autoencoder).
+- Single file: `census_lung.h5ad` (AnnData format, load with `anndata.read_h5ad` / `scanpy.read_h5ad`).
+- Full Census cell metadata retained in `.obs` (disease, cell_type, sex, donor_id, dataset_id, tissue, assay, etc.) and gene metadata in `.var` (feature_id, feature_name, feature_type).
+
+## Loading
+
+```python
+from huggingface_hub import hf_hub_download
+import anndata as ad
+
+path = hf_hub_download(repo_id="autoencodix/census-lung", repo_type="dataset", filename="census_lung.h5ad")
+adata = ad.read_h5ad(path)
+```
+
+## License and attribution
+
+Licensed **CC-BY-4.0**, per [CZ CELLxGENE Discover's data reuse policy](https://chanzuckerberg.github.io/cellxgene-census/) - every dataset admitted to Census is contributed under this license by the original authors. Attribution to the original contributing studies (not just CZI) is a term of that license. This dataset draws cells from 23 distinct publications/collections:
+
+- Sikkema et al. (2023) Nat Med — "The integrated Human Lung Cell Atlas" (31,485 cells)
+- Salcher et al. (2022) Cancer Cell — "High-resolution single-cell atlas reveals diversity and plasticity of tumor-associated neutrophils in non-small cell lung cancer" (26,179 cells)
+- Guo et al. (2023) Nat Commun — "Human CellCards Multi-Study CellRef 1.0 Atlas" (5,191 cells)
+- Xu et al. (2025) Nat Genet — "Integrated human endoderm-derived organoids cell atlas (HEOCA)" (4,188 cells)
+- "Bronchopulmonary Dysplasia" collection, no citation on file in Census (3,546 cells)
+- Natri et al. (2024) Nat Genet — "Single-cell RNA-seq analysis of Interstitial Lung Disease (ILD) subtypes" (2,266 cells)
+- Madissoon et al. (2023) Nat Genet — "A spatially resolved atlas of the human lung characterizes a gland-associated immune niche" (2,193 cells)
+- Travaglini et al. (2020) Nature — "A molecular cell atlas of the human lung from single cell RNA sequencing" (2,099 cells)
+- Lim et al. (2023) Cell Stem Cell — "Organoid modeling of human fetal lung alveolar development reveals mechanisms of cell fate patterning and neonatal respiratory disease" (1,695 cells)
+- Lukassen et al. (2020) The EMBO Journal — "SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells" (1,424 cells)
+- Melms et al. (2021) Nature — "A molecular single-cell lung atlas of lethal COVID-19" (1,377 cells)
+- Eraslan et al. (2022) Science — "Single-nucleus cross-tissue molecular reference maps to decipher disease gene function" (1,351 cells)
+- Wang et al. (2020) eLife — "LungMAP — Human data from a broad age healthy donor group" (1,099 cells)
+- The Tabula Sapiens Consortium* et al. (2022) Science — "Tabula Sapiens" (1,027 cells)
+- Dong et al. (2024) bioRxiv — "Transcriptome Analysis of Archived Tumor Tissues by Visium, GeoMx DSP, and Chromium Methods Reveals Inter- and Intra-Patient Heterogeneity" (943 cells)
+- Domínguez Conde et al. (2022) Science — "Cross-tissue immune cell analysis reveals tissue-specific features in humans" (901 cells)
+- Han et al. (2020) Nature — "Construction of a human cell landscape at single-cell level" (667 cells)
+- Lim et al. (2025) EMBO J — "A novel human fetal lung-derived alveolar organoid model reveals mechanisms of surfactant protein C maturation relevant to interstitial lung disease" (532 cells)
+- Rustam et al. (2023) Am J Respir Crit Care Med — "A Unique Cellular Organization of Human Distal Airways and Its Disarray in Chronic Obstructive Pulmonary Disease" (496 cells)
+- Wang et al. (2023) Immunity — "Emphysema Cell Atlas" (199 cells)
+- Watanabe et al. (2022) Am J Respir Cell Mol Biol — "Anomalous Epithelial Variations and Ectopic Inflammatory Response in Chronic Obstructive Pulmonary Disease" (125 cells)
+- He et al. (2022) Cell — "A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates" (43 cells)
+- Barnes et al. (2023) Sci. Immunol. — "Early human lung immune cell development and its role in epithelial cell fate" (4 cells)
+
+Full per-dataset citation and DOI details are also retained in the `dataset_id`/`dataset_id_ontology_term_id`-equivalent Census metadata; see the [CZ CELLxGENE Discover Census docs](https://chanzuckerberg.github.io/cellxgene-census/) to look up any individual `dataset_id` present in `.obs`.