This course is part of the PhD course program of the AMC Graduate School.

Course objective

The aim of this course is to get acquainted with the basic principles and algorithms of commonly used bioinformatics methods. You will gain sufficient theoretical knowledge and practical skills to be able to apply bioinformatics adequately in your own work. Topics treated include use of biological databases, statistical concepts for omics data analysis, analysis of DNA microarray and metabolomic data, use of biological networks in your analysis, and genetical genomics. The course consists of a combination of lectures and computer labs that provide you with hands-on experience with the data and techniques used for data analysis. This course provides a good introduction for our more specialized courses Bioinformatics Sequence Analysis (March 2021) and Systems Medicine (Fall 2021).

Lecturers

Schedule and course material

The course material will still be updated before the start of the course (and also during the course).

Note: to download files, right click followed by ‘save link as’

Monday, February 22, 2021
Time Type Subject Teacher Material
10.00-10.30 Lecture Introduction to Bioinformatics Perry Moerland Lecture (pptx)
10.30-12.30 Lecture Possibilities and limitations of public biological databases Aldo Jongejan Lecture (pptx)
12.30-13.30 Break
13.30-16.30 Computer lab Tutorial genome browsers Aldo Jongejan See below
Tuesday, February 23, 2021
Time Type Subject Teacher Material
10.00-12.00 Lecture Statistical concepts for omics data analysis Perry Moerland Lecture (pptx)
12.00-13.00 Break
13.00-14.00 Lecture DNA microarray analysis Perry Moerland Lecture (pptx)
14.00-17.00 Computer lab Omics data analysis Perry Moerland See below
Wednesday, February 24, 2021
Time Type Subject Teacher Material
10.30-12.30 Lecture Metabolomics Antoine van Kampen Lecture (pptx)
12.30-13.30 Break
13.30-16.30 Computer lab Metabolomics Antoine van Kampen, Eric Wever, Mia Pras-Raves, Adrie Dane See below
Thursday, February 25, 2021
Time Type Subject Teacher Material
10.00-12.00 Lecture Pathways and networks Perry Moerland Lecture (pptx)
12.00-13.00 Break
13.00-16.00 Computer lab Pathways and networks Perry Moerland See below
Friday, February 26, 2021
Time Type Subject Teacher Material
10.00-12.00 Lecture Genetical genomics Perry Moerland Lecture (pptx)
12.00-13.00 Break
13.00-14.00 Lecture Capita selecta Perry Moerland Lecture (zip)

Computer exercises

In many of the computer exercises you will use the statistical software environment R. Although most of the exercises focus on the interpretation of the results and require nothing more than copying-pasting R code, you might want to have a short look at these before or during the course week:

  • A short introduction to R
  • swirl: this package makes it fun and easy to learn R programming. Under Step 5, choose the module ‘R Programming’ to learn some of the basics of R.

For those really interested in R, twice a year we also teach the two-day Graduate School course Computing in R where we explain much of the basics of R.

Monday, February 22: Ensembl and UCSC genome browsers
Web sites
Tuesday, February 23: Omics data analysis

Download the Rmd and HTML/PDF files and open the Rmd file containing the exercises in RStudio:

  • Exercises: Rmd, HTML, PDF
  • Exercises & answers: Rmd, HTML, PDF, R
  • The files GSE14722_RAW.tar and filelist.txt can also be downloaded here
Wednesday, February 24: LC-MS metabolomics analysis
  • Exercises: PDF
  • Exercises & Answers: PDF
Thursday, February 25: Pathways and networks

Pointers

  • Bioconductor workflows: a list of example workflows for the analysis of different types of omics data using Bioconductor packages.
  • F1000Research Bioconductor channel: This channel highlights Bioconductor package-based vignettes, cross-package workflows that guide users through common and important tasks in multi-omic data analysis and integrative bioinformatics, and other articles relating to the Bioconductor project.
  • Biomedical Data Science course of Rafael Irizarry et al.