SpatialRef: a reference of spatial omics with known spot annotation

Ting Cui; Yan-Yu Li; Bing-Long Li; Han Zhang; Ting-Ting Yu; Jia-Ning Zhang; Feng-Cui Qian; Ming-Xue Yin; Qiao-Li Fang; Zi-Hao Hu; Yu-Xiang Yan; Qiu-Yu Wang; Chun-Quan Li; De-Si Shang

doi:10.1093/nar/gkae892

SpatialRef: a reference of spatial omics with known spot annotation

Nucleic Acids Res. 2024 Oct 17:gkae892. doi: 10.1093/nar/gkae892. Online ahead of print.

Authors

Ting Cui^{1

2

3}, Yan-Yu Li^{1

2

4

5

3

6}, Bing-Long Li^{1

2

3}, Han Zhang^{5

3}, Ting-Ting Yu^{5

3}, Jia-Ning Zhang^{1

2

4

3}, Feng-Cui Qian^{1

2

4

5

3

6}, Ming-Xue Yin^{1

2

3}, Qiao-Li Fang^{5

3}, Zi-Hao Hu^{5

3}, Yu-Xiang Yan^{5

3}, Qiu-Yu Wang^{1

2

4

5

3

6}, Chun-Quan Li^{1

2

4

5

3

7

6}, De-Si Shang^{1

2

4

5

3

6}

Affiliations

¹ The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
² Insititute of Biochemistry and Molecular Biology, Hengyang Medical College, University of South China, Hengyang, Hunan 421001, China.
³ The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
⁴ Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China.
⁵ School of Computer, University of South China, Hengyang, Hunan 421001, China.
⁶ The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
⁷ Key Laboratory of Rare Pediatric Diseases, Ministry of Education, University of South China, Hengyang, Hunan 421001, China.

PMID: 39417483
DOI: 10.1093/nar/gkae892

Abstract

Spatial omics technologies have enabled the creation of intricate spatial maps that capture molecular features and tissue morphology, providing valuable insights into the spatial associations and functional organization of tissues. Accurate annotation of spot or domain types is essential for downstream spatial omics analyses, but this remains challenging. Therefore, this study aimed to develop a manually curated spatial omics database (SpatialRef, https://bio.liclab.net/spatialref/), to provide comprehensive and high-quality spatial omics data with known spot labels across multiple species. The current version of SpatialRef aggregates >9 million manually annotated spots across 17 Human, Mouse and Drosophila tissue types through extensive review and strict quality control, covering multiple spatial sequencing technologies and >400 spot/domain types from original studies. Furthermore, SpatialRef supports various spatial omics analyses about known spot types, including differentially expressed genes, spatially variable genes, Gene Ontology (GO)/KEGG annotation, spatial communication and spatial trajectories. With a user-friendly interface, SpatialRef facilitates querying, browsing and visualizing, thereby aiding in elucidating the functional relevance of spatial domains within the tissue and uncovering potential biological effects.

Abstract

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