Zeng Aging Mouse clustering and mapping to the WMB taxonomy of cell types#
The Mouse Aging dataset [Jin et al] is a comprehensive single-cell RNA sequencing (scRNA-seq) dataset containing ~1.2 million high-quality single-cell transcriptomes of brain cells from young adult and aged mice of both sexes, from regions spanning the forebrain, midbrain, and hindbrain. High-resolution de novo clustering of all cells results in 847 cell clusters and reveals at least 14 age-biased clusters that are mostly glial types. Clusters in the study were mapped to the Whole Mouse Brain taxonomy (WMB-taxonomy) to provide class, subclass and supertype annotations. At the broader cell subclass and supertype levels, age-associated gene expression signatures were analyzed resulting in a list of 2,449 differentially expressed genes (age-DE genes) for many neuronal and non-neuronal cell types.
The associated metadata is hosted on AWS S3 bucket as a AWS Public Dataset:
Component |
Current Version |
Size |
---|---|---|
Metadata |
s3://allen-brain-cell-atlas/metadata/Zeng-Aging-Mouse-WMB-taxonomy/20241130 |
286 MB |
Data is being share under the CC BY NC 4.0 license.
Related resources :
Gene expression data and metadata (Zeng Aging Mouse 10Xv3)
Associated notebooks:
Getting started: Learn how to use the AbcProjectCache to facilitate data download and usage.
clustering analysis and annotation: Learn the aging mouse dataset metadata through some example use cases and visualization.
10x scRNA-seq gene expression and ageDE genes: Learn about the aging mouse gene expression and age differential expression genes through some example use cases and visualization.