A single-cell and spatial RNA-seq database for Alzheimer’s disease (ssREAD)

Cankun Wang, Diana Acosta, Megan McNutt, Jiang Bian, Anjun Ma, Hongjun Fu () and Qin Ma ()
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Cankun Wang: The Ohio State University
Diana Acosta: The Ohio State University
Megan McNutt: The Ohio State University
Jiang Bian: University of Florida
Anjun Ma: The Ohio State University
Hongjun Fu: The Ohio State University
Qin Ma: The Ohio State University

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Alzheimer’s Disease (AD) pathology has been increasingly explored through single-cell and single-nucleus RNA-sequencing (scRNA-seq & snRNA-seq) and spatial transcriptomics (ST). However, the surge in data demands a comprehensive, user-friendly repository. Addressing this, we introduce a single-cell and spatial RNA-seq database for Alzheimer’s disease (ssREAD). It offers a broader spectrum of AD-related datasets, an optimized analytical pipeline, and improved usability. The database encompasses 1,053 samples (277 integrated datasets) from 67 AD-related scRNA-seq & snRNA-seq studies, totaling 7,332,202 cells. Additionally, it archives 381 ST datasets from 18 human and mouse brain studies. Each dataset is annotated with details such as species, gender, brain region, disease/control status, age, and AD Braak stages. ssREAD also provides an analysis suite for cell clustering, identification of differentially expressed and spatially variable genes, cell-type-specific marker genes and regulons, and spot deconvolution for integrative analysis. ssREAD is freely available at https://bmblx.bmi.osumc.edu/ssread/ .

Date: 2024
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DOI: 10.1038/s41467-024-49133-z

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