Module 0: Environment Setup
Single Cell Workshop
2026-01-15
Source:vignettes/00_setup.Rmd
00_setup.RmdIntroduction
Welcome to the Single Cell RNA-Sequencing Workshop. This document guides you through setting up your R environment before the workshop begins.
Please complete this setup at least one day before the workshop. Package installation takes approximately 10-15 minutes, and data download takes approximately 5 minutes depending on your internet connection.
What We Will Set Up
-
R packages using
renvfor reproducibility - Workshop data downloaded from Zenodo (~420 MB)
System Requirements
| Resource | Minimum | Recommended |
|---|---|---|
| RAM | 8 GB | 16 GB |
| Disk space | 5 GB free | 10 GB free |
| R version | 4.3+ | 4.5+ |
| RStudio | 2023.06+ | Latest |
Check your R version:
R.version.string## [1] "R version 4.5.2 (2025-10-31)"If your R version is older than 4.3, please update from CRAN before proceeding.
Step 1: Clone or Download the Repository
First, obtain the workshop materials:
Option A: Clone with Git (Recommended)
Option B: Download ZIP
- Visit https://github.com/phipsonlab/single_cell_workshop
- Click the green “Code” button
- Select “Download ZIP”
- Extract the ZIP file
Then open single_cell_workshop.Rproj in RStudio.
Step 2: Install Packages with renv
This workshop uses renv for reproducible package
management. All package versions are locked in renv.lock,
ensuring everyone has identical environments.
When you open the project in RStudio, renv should automatically bootstrap itself. If prompted to install renv, select “Yes”.
Then run:
# Install all packages with exact versions from renv.lock
# This may take 10-15 minutes on first run
renv::restore()When prompted “Do you want to proceed?”, type y and
press Enter.
Step 3: Verify Package Installation
After renv::restore() completes, verify that all
critical packages are installed:
packages <- c("Seurat", "harmony", "glmGamPoi", "edgeR", "limma", "speckle")
check <- sapply(packages, requireNamespace, quietly = TRUE)## Warning: replacing previous import 'S4Arrays::makeNindexFromArrayViewport' by
## 'DelayedArray::makeNindexFromArrayViewport' when loading 'SummarizedExperiment'
missing <- names(check)[!check]
if (length(missing) == 0) {
message("All critical packages installed successfully!")
} else {
message("WARNING: Missing packages: ", paste(missing, collapse = ", "))
message("Try running renv::restore() again.")
}## All critical packages installed successfully!Step 4: Download Workshop Data
The workshop data files are hosted on Zenodo. Run the following code to download them:
# Zenodo record for workshop data
zenodo_url <- "https://zenodo.org/records/18237749/files/"
files <- c("heart-counts.Rds", "cellinfo_updated.Rds")
# Create data directory if needed
if (!dir.exists("data")) dir.create("data")
# Download each file
for (f in files) {
dest <- file.path("data", f)
if (file.exists(dest)) {
message(f, " already exists, skipping")
next
}
message("Downloading ", f, "...")
download.file(
url = paste0(zenodo_url, f, "?download=1"),
destfile = dest,
mode = "wb"
)
}
message("Download complete!")Note: Total download size is approximately 420 MB.
Step 5: Final Verification
Run this final check to ensure everything is ready:
cat("=== Workshop Setup Verification ===\n\n")## === Workshop Setup Verification ===
# Check R version
cat("R Version:", R.version.string, "\n\n")## R Version: R version 4.5.2 (2025-10-31)
# Check critical packages
cat("Package Status:\n")## Package Status:
packages <- c("Seurat", "harmony", "glmGamPoi", "edgeR", "limma", "speckle")
for (pkg in packages) {
status <- if (requireNamespace(pkg, quietly = TRUE)) "OK" else "MISSING"
cat(sprintf(" %-12s %s\n", pkg, status))
}## Seurat OK
## harmony OK
## glmGamPoi OK
## edgeR OK
## limma OK
## speckle OK
# Check data files
cat("\nData Files:\n")##
## Data Files:
data_dir <- if (dir.exists("data")) "data" else "../data"
for (f in c("heart-counts.Rds", "cellinfo_updated.Rds")) {
path <- file.path(data_dir, f)
status <- if (file.exists(path)) "FOUND" else "NOT FOUND"
cat(sprintf(" %-25s %s\n", f, status))
}## heart-counts.Rds FOUND
## cellinfo_updated.Rds FOUND
cat("\n================================\n")##
## ================================Troubleshooting
renv::restore() fails
If renv::restore() encounters errors:
- Restart R (Session > Restart R)
- Run
renv::restore()again - If specific packages fail, try installing them manually then run
renv::restore()
Memory errors
If you encounter “cannot allocate vector” errors:
- Close other applications
- Restart R
- Try again
Package conflicts
If you have existing packages causing conflicts:
# Use a clean renv library
renv::rebuild()Getting Help
If you cannot resolve setup issues:
- Note the exact error message
- Run
sessionInfo()and save the output - Contact the workshop organisers before the session
Session Information
## R version 4.5.2 (2025-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.3 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
## [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
## [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
## [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
##
## time zone: UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices datasets utils methods base
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3 jsonlite_2.0.0
## [3] magrittr_2.0.4 spatstat.utils_3.2-1
## [5] farver_2.1.2 rmarkdown_2.30
## [7] fs_1.6.6 ragg_1.5.0
## [9] vctrs_0.6.5 ROCR_1.0-11
## [11] spatstat.explore_3.6-0 S4Arrays_1.10.1
## [13] htmltools_0.5.9 SparseArray_1.10.8
## [15] sass_0.4.10 sctransform_0.4.3
## [17] parallelly_1.46.1 KernSmooth_2.23-26
## [19] bslib_0.9.0 htmlwidgets_1.6.4
## [21] desc_1.4.3 ica_1.0-3
## [23] plyr_1.8.9 speckle_1.10.0
## [25] plotly_4.11.0 zoo_1.8-15
## [27] cachem_1.1.0 igraph_2.2.1
## [29] mime_0.13 lifecycle_1.0.5
## [31] pkgconfig_2.0.3 Matrix_1.7-4
## [33] R6_2.6.1 fastmap_1.2.0
## [35] MatrixGenerics_1.22.0 fitdistrplus_1.2-4
## [37] future_1.68.0 shiny_1.12.1
## [39] digest_0.6.39 patchwork_1.3.2
## [41] S4Vectors_0.48.0 Seurat_5.4.0
## [43] tensor_1.5.1 RSpectra_0.16-2
## [45] irlba_2.3.5.1 GenomicRanges_1.62.1
## [47] textshaping_1.0.4 beachmat_2.26.0
## [49] progressr_0.18.0 spatstat.sparse_3.1-0
## [51] httr_1.4.7 polyclip_1.10-7
## [53] abind_1.4-8 compiler_4.5.2
## [55] S7_0.2.1 fastDummies_1.7.5
## [57] MASS_7.3-65 DelayedArray_0.36.0
## [59] tools_4.5.2 lmtest_0.9-40
## [61] otel_0.2.0 httpuv_1.6.16
## [63] future.apply_1.20.1 goftest_1.2-3
## [65] glmGamPoi_1.22.0 glue_1.8.0
## [67] nlme_3.1-168 promises_1.5.0
## [69] grid_4.5.2 Rtsne_0.17
## [71] cluster_2.1.8.1 reshape2_1.4.5
## [73] generics_0.1.4 gtable_0.3.6
## [75] spatstat.data_3.1-9 tidyr_1.3.2
## [77] data.table_1.18.0 XVector_0.50.0
## [79] sp_2.2-0 BiocGenerics_0.56.0
## [81] spatstat.geom_3.6-1 RcppAnnoy_0.0.23
## [83] ggrepel_0.9.6 RANN_2.6.2
## [85] pillar_1.11.1 stringr_1.6.0
## [87] limma_3.66.0 spam_2.11-3
## [89] RcppHNSW_0.6.0 later_1.4.5
## [91] splines_4.5.2 dplyr_1.1.4
## [93] lattice_0.22-7 renv_1.1.5
## [95] survival_3.8-3 deldir_2.0-4
## [97] tidyselect_1.2.1 SingleCellExperiment_1.32.0
## [99] locfit_1.5-9.12 miniUI_0.1.2
## [101] pbapply_1.7-4 knitr_1.51
## [103] gridExtra_2.3 Seqinfo_1.0.0
## [105] IRanges_2.44.0 edgeR_4.8.2
## [107] SummarizedExperiment_1.40.0 scattermore_1.2
## [109] stats4_4.5.2 xfun_0.55
## [111] Biobase_2.70.0 statmod_1.5.1
## [113] matrixStats_1.5.0 stringi_1.8.7
## [115] lazyeval_0.2.2 yaml_2.3.12
## [117] evaluate_1.0.5 codetools_0.2-20
## [119] tibble_3.3.1 BiocManager_1.30.27
## [121] cli_3.6.5 uwot_0.2.4
## [123] xtable_1.8-4 reticulate_1.44.1
## [125] systemfonts_1.3.1 jquerylib_0.1.4
## [127] harmony_1.2.4 Rcpp_1.1.1
## [129] globals_0.18.0 spatstat.random_3.4-3
## [131] png_0.1-8 spatstat.univar_3.1-5
## [133] parallel_4.5.2 pkgdown_2.2.0
## [135] ggplot2_4.0.1 dotCall64_1.2
## [137] listenv_0.10.0 viridisLite_0.4.2
## [139] scales_1.4.0 ggridges_0.5.7
## [141] SeuratObject_5.3.0 purrr_1.2.1
## [143] rlang_1.1.7 cowplot_1.2.0