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1 | 1 | # AgingMouseBrainCCInx |
| 2 | +# Single-cell transcriptomic profiling of the aging mouse brain |
| 3 | +Methodios Ximerakis, Scott L. Lipnick, Brendan T. Innes, Sean K. Simmons, Xian |
| 4 | +Adiconis, Danielle Dionne, Brittany A. Mayweather, Lan Nguyen, Zachary Niziolek, |
| 5 | +Ceren Ozek, Vincent L. Butty, Ruth Isserlin, Sean M. Buchanan, Stuart S. Levine, |
| 6 | +Aviv Regev, Gary D. Bader, Joshua Z. Levin, and Lee L. Rubin. |
| 7 | + |
| 8 | +## Abstract |
| 9 | +The mammalian brain is complex, with multiple cell types performing a variety of diverse |
| 10 | +functions, but exactly how the brain is affected with aging remains largely unknown. Here |
| 11 | +we performed a single-cell transcriptomic analysis of young and old mouse brains. We |
| 12 | +provide a comprehensive dataset of aging-related genes, pathways and ligand-receptor |
| 13 | +interactions in nearly all brain cell types. Our analysis identified gene signatures that vary |
| 14 | +in a coordinated manner across cell types and gene sets that are regulated in a cell type |
| 15 | +specific manner, even at times in opposite directions. Thus, our data reveal that aging, |
| 16 | +rather than inducing a universal program, drives a distinct transcriptional course in each |
| 17 | +cell population. These data provide an important resource for the aging community and |
| 18 | +highlight key molecular processes, including ribosome biogenesis, underlying aging. We |
| 19 | +believe that this large-scale dataset, which is publicly accessible online ([aging-mouse-brain](https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain)), |
| 20 | +will facilitate additional discoveries directed towards understanding and modifying |
| 21 | +the aging process. |
2 | 22 |
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3 | 23 | ## Usage |
4 | 24 | This is an R package used to explore the cell-cell interaction predictions from the |
5 | | -paper "Single-cell transcriptomic profiling of the aging mouse brain". The |
6 | | -package contains an RData list object with both the edge list and node |
| 25 | +paper. The package contains an RData list object with both the edge list and node |
7 | 26 | metadata of predicted cell-cell interactions between cell types in the mouse |
8 | 27 | brain, and their changes with aging. The predictions were generated using |
9 | 28 | CCInx (baderlab.github.io/CCInx). You can install this package in R by running: |
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