This GitHub repository documents the core analyses of a spatiotemporal RNA-seq study on mouse brain aging, including 1,076 samples from 15 regions spanning 7 ages and two rejuvenating interventions.
If an interactive version of the data is preferred, please visit our Shiny-App: https://twc-stanford.shinyapps.io/spatiotemporal_brain_map/
We recommend to re-create the directory setup provided here, consisting of:
- Rscripts - a folder where the core scripts are stored
- input_data - a folder containing raw counttables, metadata etc. We provide here only the bulkseq data, as single-cell/spatial data exceed the size limit
- R_objects - a folder where processed R objects, such as Deseq2 objects are stored so they can be loaded again by later analyses
- Signature_repository - a folder where we store VISION score objects in the form of R.bin files that can be loaded when needed
- Output_tables - at some points in the scripts, we create e.g. lists of genes. These sould be stored here
If using data or scripts of this study, please cite the following pre-print:
A spatiotemporal map of the aging mouse brain reveals white matter tracts as vulnerable foci.
Oliver Hahn, Aulden G Foltz, Micaiah Atkins, Blen Kedir, Patricia Moran-Losada, Ian H Guldner, Christy Munson, Fabian Kern, Róbert Pálovics, Nannan Lu, Achint Kaur, Jacob Hull, John R Huguenard, Andreas Keller, Benoit Lehallier, Tony Wyss-Coray. bioRxiv. doi: https://doi.org/10.1101/2022.09.18.508419
The sequencing datasets analyzed during the current study are available in the Gene Expression Omnibus repository under accession numbers GSE212336, GSE212576, GSE212903, GSE227689 and GSE227515.
The analyses were performed within an R 3.6 enviornment.
R version 3.6.3 (2020-02-29) Platform: x86_64-apple-darwin15.6.0 (64-bit) Running under: OS X 13.2
The following packages and versions are required and should be loaded prior to running the analysis
Biobase_2.46.0
BiocGenerics_0.32.0
BiocParallel_1.20.1
ComplexUpset_1.3.3
DelayedArray_0.12.3
DESeq2_1.26.0
dplyr_1.0.9
emmeans_1.7.5
GenomeInfoDb_1.22.1
GenomicRanges_1.38.0
GEOquery_2.54.1
ggplot2_3.3.6
ggrepel_0.9.1
gplots_3.1.3
gprofiler2_0.2.1
IRanges_2.20.2
limma_3.42.2
lsmeans_2.30-0
matrixStats_0.62.0
pheatmap_1.0.12
plyr_1.8.7
RColorBrewer_1.1-3
readr_2.1.2
reshape2_1.4.4
rstatix_0.7.0
S4Vectors_0.24.4
scales_1.2.0
Seurat_3.1.2
SummarizedExperiment_1.16.1
tidyr_1.2.0
umap_0.2.8.0
Vennerable_3.1.0.9000
VISION_3.0.0
WGCNA_1.70-3
zoo_1.8-9