Datasets:
pretty_name: SpatialDataAgent-DB Public Catalog
license: other
license_name: source-specific-data-terms
license_link: >-
https://huggingface.co/datasets/Biogod/SpatialDataAgent-DB#data-use-and-source-terms
tags:
- biology
- spatial-transcriptomics
- metadata
configs:
- config_name: samples
data_files: catalog/samples.parquet
SpatialDataAgent-DB Public Catalog
Left to right: H&E and GFAP from the same Visium section (GSM9721856), Xenium DAPI (GSM9301054), and a CosMx composite (GSM9372712). The GFAP panel displays all 3,416 recorded spots using the existing log1p preview values.
Search and inspect the metadata for 12,163 samples, 1,265 published study folders and 635,240,170 spatial observations in the fixed sda-unified-20261010-v3 snapshot. It includes 8,211 samples with released tissue images.
This repository contains metadata only. Full sample data require manual access approval and are currently being uploaded. The metadata catalog's presence does not imply that the full upload is complete.
catalog/samples.parquet and samples.csv provide the original release index, including repository-relative sample_dir paths and source content hashes. Study metadata and source-bound biological/audit annotations are included as atlas-study-metadata.jsonl and atlas-sample-metadata.jsonl.
Reported vocabulary and age units are not harmonized. Missing biological metadata and review states remain explicit. Counts capability, source verification, image registration and human review describe different checks. Observations are spots, cells, bins or beads, not independent donors.
Source index SHA256: 909c4ec50e71c636eadc7bf01a9479fef1b4fd480ac348dfea6b785e566c7bed. See the main Dataset Card for data organization, quality distinctions, splits, provenance and source-specific reuse terms.
Collection composition
Sample counts by platform, image availability, source collection and retained split (n = 12,163; source snapshot: sda-unified-20261010-v3).
Access and reuse
Browse the public catalog, request access to the full sample data, then retrieve H5AD, available TIFF images and JSON metadata. AnnData/Scanpy can read downloaded expression files. Streaming training shards and the Python SDK are planned follow-up outputs.