Datasets:

Shaow
/

mousebrain_visium_3section

license: mit
language:
  - en
tags:
  - spatial-transcriptomics
  - 10x
  - mus
pretty_name: Mouse Brain Visium · 3 complementary sections
size_categories:
  - 10K<n<100K

    # Mouse Brain Visium · 3 complementary sections

    Curated, ready-to-load spatial transcriptomics dataset.

    ## Source

    - Paper: [10x Genomics public datasets](https://www.10xgenomics.com/datasets)
    - Canonical download: cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_*

    ## Scale

    | Property | Value |
    |---|---|
    | Technology | 10x Genomics Visium |
    | Species | Mus musculus |
    | Tissue | Mouse brain (sagittal anterior, sagittal posterior, coronal) |
    | Sections / slices | 3 |
    | Total cells / spots | 8,816 |

    ## Files

    - `Visium_sagittal-anterior2/V1_Mouse_Brain_Sagittal_Anterior_Section_2_filtered_feature_bc_matrix.h5`

Visium_sagittal-posterior2/V1_Mouse_Brain_Sagittal_Posterior_Section_2_filtered_feature_bc_matrix.h5

Visium_coronal/V1_Adult_Mouse_Brain_filtered_feature_bc_matrix.h5

  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)

  `in_tissue`, `array_row`, `array_col`

  ## Notes

  Three 10x Visium mouse-brain serial sections offering complementary tissue views. Original 10x outputs (filtered h5 + spatial/) kept in conventional subfolders so `sc.read_visium(folder)` works directly. After filtering to in_tissue==1: 2825 / 3289 / 2702 spots respectively.

  ## Usage

  ```python

import scanpy as sc from huggingface_hub import snapshot_download d = snapshot_download(repo_id='Shaow/mousebrain_visium_3section', repo_type='dataset') adata_st_list = [] for sub, h5 in [ ('Visium_sagittal-anterior2', 'V1_Mouse_Brain_Sagittal_Anterior_Section_2_filtered_feature_bc_matrix.h5'), ('Visium_sagittal-posterior2', 'V1_Mouse_Brain_Sagittal_Posterior_Section_2_filtered_feature_bc_matrix.h5'), ('Visium_coronal', 'V1_Adult_Mouse_Brain_filtered_feature_bc_matrix.h5'), ]: a = sc.read_visium(f'{d}/{sub}', count_file=h5) a.var_names_make_unique() adata_st_list.append(a[a.obs['in_tissue'] == 1].copy())



        ## 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.