Datasets:

Shaow
/

dlpfc_visium_4slice

license: mit
language:
  - en
tags:
  - spatial-transcriptomics
  - 10x
  - homo
pretty_name: Human DLPFC Visium · 4 adjacent slices
size_categories:
  - 10K<n<100K

    # Human DLPFC Visium · 4 adjacent slices

    Curated, ready-to-load spatial transcriptomics dataset.

    ## Source

    - Paper: [Maynard et al., Nat. Neurosci. 2021](https://www.nature.com/articles/s41593-020-00787-0)
    - Canonical download: spatialLIBD R package · slices 151673–151676

    ## Scale

    | Property | Value |
    |---|---|
    | Technology | 10x Genomics Visium |
    | Species | Homo sapiens |
    | Tissue | Human dorsolateral prefrontal cortex |
    | Sections / slices | 4 |
    | Total cells / spots | 14,243 |

    ## Files

    - `h5ad/adata_1.h5ad`

h5ad/adata_2.h5ad
h5ad/adata_3.h5ad

h5ad/adata_4.h5ad

  Each `.h5ad` follows the AnnData spec:
  - `.X` — gene expression matrix (cells × genes), sparse where natural
  - `.obs` — per-cell annotations (see "Metadata" below)
  - `.obsm['spatial']` — `(n_cells, 2)` float32 spatial coordinates
  - (where present) `.layers['count']` — raw integer counts
  - (where present) `.obsm['spatial3d']` — `(n_cells, 3)` float32 (x, y, z=section)

  ## Metadata (`obs` columns)

  `layer`, `in_tissue`, `array_row`, `array_col`

  ## Notes

  4 of the 12-slice Maynard atlas (slices 151673–151676), preprocessed as ready-to-load AnnData. `obs['layer']` carries the manual L1–L6 + WM annotation.

  ## Usage

  ```python

import scanpy as sc from huggingface_hub import snapshot_download d = snapshot_download(repo_id='Shaow/dlpfc_visium_4slice', repo_type='dataset') adata_st_list = [sc.read_h5ad(f'{d}/h5ad/adata_{i}.h5ad') for i in range(1, 5)]



        ## Citation

        If you use this dataset, please cite the source paper above.

        ## License

        MIT for the curation/preparation. Underlying data inherits the license of
        the upstream publication (typically CC-BY-4.0); please see the source paper.