A Purkinje cell to parabrachial nucleus pathway enables broad cerebellar influence over the forebrain and emotional valence
Creators
- 1. Department of Neurobiology, Harvard Medical School, Boston, MA USA
- 2. Department of Medicine, Division of Endocrinology, Diabetes and Metabolism. Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
- 3. Broad Institute of Harvard and MIT, Stanley Center for Psychiatric Research, Cambridge, MA, USA
- 4. Broad Institute of Harvard and MIT, Stanley Center for Psychiatric Research, Cambridge, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
Description
OVERVIEW
The following README contains: i) the raw count matrix relative to all nuclei of the dataset, called “filtered_feature_bc_matrix”; ii) the cell cycle genes lists (G2/M and S phase specific markers) named “cycle_gene”; iii) the markers gene lists used to generate the Dot Plots for the All_cells and Neuronal clustering (glial and neuronal markers); iv) the instruction to set up an R environment (R version 4.1.2) and to install R Studio on a Windows/macOS operative systems; iii) the instructions to install Seurat 3.2.3 along with all its dependencies; iv) the software code used to generate all the plots and figure as showed in the manuscript.
SYSTEM REQUIREMENTS
The following analysis can be performed on a standard computer with sufficient RAM to support the in-memory operation required by Seurat 3.2.3. The installation of Seurat 3.2.3 and all its dependencies have been tested on both Windows (version 10 64-bit ) and macOS (Big Sur version 11.6.1) operating systems.
ALL PACKAGES and DEPENDENCIES
R version 4.1.2 (2021-11-01)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.2.1
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_1.0.8 scales_1.1.1 RColorBrewer_1.1-2 viridis_0.6.2 viridisLite_0.4.0 ggplot2_3.3.5 Matrix_1.3-4
[8] biomaRt_2.50.3 Seurat_3.2.3
loaded via a namespace (and not attached):
[1] BiocFileCache_2.2.1 plyr_1.8.6 igraph_1.2.11 lazyeval_0.2.2 splines_4.1.2
[6] listenv_0.8.0 scattermore_0.8 GenomeInfoDb_1.30.1 digest_0.6.29 htmltools_0.5.2
[11] fansi_1.0.2 magrittr_2.0.3 memoise_2.0.1 tensor_1.5 cluster_2.1.2
[16] ROCR_1.0-11 limma_3.50.1 remotes_2.4.2 globals_0.14.0 Biostrings_2.62.0
[21] matrixStats_0.61.0 prettyunits_1.1.1 colorspace_2.0-3 blob_1.2.2 rappdirs_0.3.3
[26] ggrepel_0.9.1 crayon_1.5.0 RCurl_1.98-1.6 jsonlite_1.8.0 spatstat_1.64-1
[31] spatstat.data_2.1-2 survival_3.2-13 zoo_1.8-9 glue_1.6.2 polyclip_1.10-0
[36] gtable_0.3.0 zlibbioc_1.40.0 XVector_0.34.0 leiden_0.3.9 future.apply_1.8.1
[41] BiocGenerics_0.40.0 abind_1.4-5 DBI_1.1.2 miniUI_0.1.1.1 Rcpp_1.0.8
[46] xtable_1.8-4 progress_1.2.2 reticulate_1.24 bit_4.0.4 rsvd_1.0.5
[51] stats4_4.1.2 htmlwidgets_1.5.4 httr_1.4.2 ellipsis_0.3.2 ica_1.0-2
[56] pkgconfig_2.0.3 XML_3.99-0.9 farver_2.1.0 uwot_0.1.11 dbplyr_2.1.1
[61] deldir_1.0-6 utf8_1.2.2 tidyselect_1.1.2 labeling_0.4.2 rlang_1.0.2
[66] reshape2_1.4.4 later_1.3.0 AnnotationDbi_1.56.2 munsell_0.5.0 tools_4.1.2
[71] cachem_1.0.6 cli_3.2.0 generics_0.1.2 RSQLite_2.2.10 pacman_0.5.1
[76] ggridges_0.5.3 stringr_1.4.0 fastmap_1.1.0 goftest_1.2-3 bit64_4.0.5
[81] fitdistrplus_1.1-6 purrr_0.3.4 RANN_2.6.1 KEGGREST_1.34.0 sceasy_0.0.6
[86] pbapply_1.5-0 future_1.24.0 nlme_3.1-153 mime_0.12 xml2_1.3.3
[91] compiler_4.1.2 rstudioapi_0.13 plotly_4.10.0 filelock_1.0.2 curl_4.3.2
[96] png_0.1-7 spatstat.utils_2.3-0 tibble_3.1.6 stringi_1.7.6 lattice_0.20-45
[101] vctrs_0.3.8 pillar_1.7.0 lifecycle_1.0.1 BiocManager_1.30.16 lmtest_0.9-39
[106] RcppAnnoy_0.0.19 data.table_1.14.2 cowplot_1.1.1 bitops_1.0-7 irlba_2.3.5
[111] httpuv_1.6.5 patchwork_1.1.1 R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-20
[116] gridExtra_2.3 IRanges_2.28.0 parallelly_1.30.0 codetools_0.2-18 MASS_7.3-54
[121] assertthat_0.2.1 withr_2.5.0 sctransform_0.3.3 S4Vectors_0.32.3 GenomeInfoDbData_1.2.7
[126] mgcv_1.8-38 parallel_4.1.2 hms_1.1.1 grid_4.1.2 rpart_4.1-15
[131] tidyr_1.2.0 Rtsne_0.15 Biobase_2.54.0 shiny_1.7.1
SOFTWARE INSTALLATION GUIDE
1. R version 4.1.2 for Windows and for macOS can be downloaded at: https://cran.rstudio.com/.
2. All packages used can be installed running the following command install.packages() from R console.
3. Seurat 3.2.3 and all its dependencies can be installed running the following command line: remotes::install_version("Seurat", version = "3.2.3").
4. A typical installation time on a “normal” desktop computer is around 15-20 minutes.
INSTRUCTION FOR USE/EXPECTED OUTPUT/EXPECTED RUN TIME
All the instructions to install and run the code on the data provided in this folder are in the document “SCRIPT.txt”. The expected outputs of the code are: 1) “NEURONS_markers.csv”; 2) Figure 5; 3) Supplementary Figure 12. Expected run time is about 10 min for all the analyses.