1 Practical matters

1.1 Course website

1.2 Lectures

1.3 Exam

  • 2 ECTS credits
  • Two exam sessions: 08.04.2020 and 27.05.2020, each 1 hour (first hour)
  • 12 multiple choice question per exam
  • To pass: score >= 50% overall, i.e. at least 12 out of 24 questions correct
  • Computer required (i.e. some multipe-choice questions require a bit of coding)
  • All material allowed, communication strictly prohibited

1.4 Learning goals

  • Understand the basic concepts involved in the analysis of genomic data (bulk and single-cell mRNA-Seq, ATAC-Seq, ChIP-Seq)
  • Be able to perform some simple analysis workflow using the Bioconductor framework, visualize and interpret the results.

1.5 Important

  • Asking questions is highly encouraged
  • If something is not working or understood, reach out for help as early as possible
  • Practice, practice and practice again!

1.6 Requirements

A basic knowledge of R and RStudio

  • Understand the usage of basic data types such as factor or data.frame
  • Load, modify and summarize data fitting into a data.frame
  • Visualize the data, e.g., as a scatterplot or boxplot
  • Run and interpret a simple linear model
  • Understand error messages and get help from the documentation

1.7 Resources for catching-up (and for future reference)

If you find today’s exercises too challenging you will have to catch up fast. Here are a few resources:

1.7.1 Online resources

1.7.2 Books

  • The R chapters in: Buffalo V (2015) Bioinformatics data skills. O’Reilly. SwissBib link
  • Dalgaard P (2008) Introductory statistics with R. Springer Science & Business Media. SwissBib link

1.7.3 R Cheat sheets

Various cheat sheets at the RStudio website, for example:

2 RStudio and best practices

  • RStudio is an Integrated Development Environment (IDE) for the R programming language.
  • It is one of the most productive option for learning and using R
  • It enables interactive data analysis, reproducible research and result publishing
  • It can be locally installed (desktop version) or accessed via a web browser (RStudio server).

2.1 Installation and setup

  • See the course webpage for the different options
  • R needs to be up-to-date (version >= 3.6.0)
  • Ask for help if you encounter troubles

2.2 The RStudio interface