IPVW/ICES single-cell course 2021-2022

1 Course Description

High-throughput ’omics studies generate ever larger datasets and, as a consequence, complex data interpretation challenges. This course focusses on statistical concepts involved in preprocessing, quantification, normalization, visualization, integration and differential analysis of single-cell ’omics data. The course will rely exclusively on free and user-friendly open-source tools in R/Bioconductor. We hope that this will provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard data analysis workflows for proteomics and next-generation sequencing applications.

2 Prerequisites

The prerequisites are the successful completion of a basic course of statistics that covers topics on data exploration and descriptive statistics, statistical modeling, and inference: linear models, confidence intervals, t-tests, F-tests, anova, chi-squared test. The basis concepts may be revisited in the online course at https://gtpb.github.io/PSLS20/ (English) and in https://statomics.github.io/statistiekCursusNotas/ (Dutch).

In addition, knowledge of programming in R is preferred. A primer to R and Data visualization in R can be found at:

• R Basics: https://dodona.ugent.be/nl/courses/335/
• R Data Exploration: https://dodona.ugent.be/nl/courses/345/

3 Software

• Participants are required to bring their own laptop with R version 4.1.1 or greater.

• We also recommend to also install the latest version of RStudio.

• Participants who have issues with the installation of the R/Rstudio can use an Rstudio instance in the cloud with all packages installed for the course in the mean time. Note, that this is instance is not for routine use.

4 DropBox link

We have created a DropBox folder containing convenience files, e.g., a preprocessed SingleCellExperiment that is the end result of lab session 1.

5 Detailed Program

0. Positioning of the course: slides.

5.1 Theory Session I (Nov. 17, 2021)

1. Lecture: A brief introduction to sequencing technology: HTML, [PDF].
2. Lecture: The two most popular single-cell RNA-seq protocols: HTML, [PDF].
3. Lecture: single-cell RNA-seq analysis: general concepts and workflow: slides.

6 Instructors

• Koen Van den Berge
• Jeroen Gilis

7 License

This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

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This work is licensed under the CC BY-NC-SA 4.0 licence.