A single-cell and spatial RNA-seq database for Alzheimer's disease (ssREAD).
Cankun WangDiana AcostaMegan McNuttJiang BianAnjun MaHongjun FuQin MaPublished in: Nature communications (2024)
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/ .
Keyphrases
- single cell
- rna seq
- high throughput
- cognitive decline
- genome wide
- induced apoptosis
- body mass index
- electronic health record
- endothelial cells
- emergency department
- bioinformatics analysis
- mesenchymal stem cells
- oxidative stress
- adverse drug
- gene expression
- blood brain barrier
- brain injury
- dna methylation
- case control
- mass spectrometry
- big data
- signaling pathway
- resting state
- weight gain
- subarachnoid hemorrhage
- functional connectivity
- genome wide analysis
- cerebral ischemia
- genome wide identification