A user-friendly and comprehensive searchable database has been developed by neuroscience and biomedical informatics researchers at The Ohio State University Wexner Medical Center and College of Medicine. The database, called ssREAD, is now available for free and is designed to aid in the study of Alzheimer’s disease. This information was published in a manuscript in Nature Communications.Alzheimer’s disease is responsible for the majority of dementia cases, with up to 80% attributed to it. According to the Alzheimer’s Association’s 2023 report on Alzheimer’s disease facts and figures, an estimated 6.7 million Americans aged 65 and older are currently living with Alzheimer’s dementia.
This database is designed to aid in the study of Alzheimer’s disease pathology, which involves investigating the cause, progression, structural and functional changes, and natural history of the disease.
Advances in molecular research have led to a greater understanding of the molecular signatures that underlie Alzheimer’s disease pathology, using techniques such as single-cell and single-nucleus RNA-sequencing (scRNA-seq & snRNA-seq) and sp.
“These technologies have provided new insights into the study of Alzheimer’s disease development and the differences between sexes at the cellular and molecular levels. Our ssREAD repository offers a wider range of datasets related to Alzheimer’s disease, along with an improved analytical pipeline and usability,” explained Dr. Hongjun “Harry” Fu, assistant professor of neuroscience at Ohio State and co-corresponding author of the study.
Datasets
The database includes 277 integrated datasets from 67 studies related to Alzheimer’s disease using single-cell RNA sequencing and single-nucleus RNA sequencing, totaling 7.3The repository contains 32,202 cells and 381 spatial transcriptomics samples from 85 human and mouse studies. It includes detailed annotations of cell types and spatial layers, as well as differential gene expressions and functional enrichment analysis. The repository also provides information on spatially variable genes and deconvolution with single-cell datasets.
Additionally, it offers interactive visualizations such as scatter plots for clusters, cell types, and spatial layers, as well as feature plots and violin plots for gene analysis. The user-friendly web server provides comprehensive analysis interpretations and filters that support multiple selections.
- expression profile
- Real-time gene set enrichment analysis
“We are narrowing the divide for researchers by establishing this specialized database. Incorporating these varied datasets and conditions will be extremely valuable for researchers investigating the intricate landscape of Alzheimer’s disease,” stated Qin Ma, PhD, professor in Ohio State’s department of biomedical informatics.
