Single Cell RNA-seq Analysis Workshop
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  • Software Setup
  • Schedule
  • Materials
  • Datasets
  • Cheat Sheets
  • Additional Resources

Workshop Reference Material

Background reading and reference material the workshop’s chapters cite into — single-cell biology, statistics, shell scripting, Git, databases, file formats, and a methods-section template. Read what you need, when you need it.

These materials support the core workshop but are not part of the three-day sequence — they’re linked from Additional Resources. Quick one-page references (R, Seurat, ggplot2, SLURM, Git…) are on the separate Cheat Sheets tab.

Note

Getting up and running (R, the command line, computers & HPC). That material is now the two Day 0 modules — work them before the workshop if any of it is rusty:

  • P1 — Computer Systems & the Command Line — how computers and operating systems work, using VS Code on your own laptop, and the command line (navigation, paths, pipes). (The Talapas cluster track — VS Code Remote-SSH, Lmod, SLURM, and reproducible environments — is Module 09 on Friday.)
  • P2 — R & RStudio — R, RStudio, data structures, functions, the tidyverse, reading/writing data.

Appendices — reference material

Listed in the order they tend to come up across the workshop flow.

# Appendix Topic
A Single-Cell Biology Refresher The molecular biology behind scRNA-seq — read this before Lecture 00 if your bio is rusty
B Statistical Foundations NB / Poisson, design matrices, FDR, shrinkage, why per-cell tests fail
C GREP, Regular Expressions & Shell Scripting Pattern matching with grep, regex syntax, writing reusable shell scripts
D Git, GitHub & Version Control Tracking changes with Git, collaborating on GitHub, common workflows
E Gene-Expression Databases & File Formats The big-six scRNA-seq repositories and a field guide to every file format
F Common Bioinformatics File Formats A field guide to FASTA, FASTQ, SAM/BAM, GFF3/GTF, BED, VCF, BigWIG, and the single-cell containers — with annotated head-of-file examples
G Methods-Section Template Annotated boilerplate for an scRNA-seq paper’s methods section
H Core R Commands Reference A task-organised look-up for the R you use in every tutorial — vectors, data frames, dplyr, ggplot2, reading/writing data
I Quarto & Markdown Syntax The markup behind every page here — headings, code chunks & options, figures, callouts, tabsets, math, and citations

The Glossary of single-cell terminology is at the top of the Additional Resources page; read it alongside the lectures.

How to use these resources

Tip

Read on demand. The workshop chapters cross-reference these liberally — when a chapter says “see Appendix B § 8 for why per-cell DE fails”, that’s a hint to read that section before continuing.

If you’re new to the toolchain: start with the two Day 0 modules (R, the command line, computers & HPC) before Day 1.

If your molecular biology is rusty: Appendix A, before Lecture 00.

If your statistics is rusty: Appendix B, before Lecture 05 / Chapter 5.

Once you start writing up your own scRNA-seq results: keep Appendix G (Methods-Section Template) open in another tab.

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