This course is part of the PhD course program of the AMC Graduate School.
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).
- Dr. ir. Perry Moerland (Coordinator; Bioinformatics Laboratory, Amsterdam UMC, location AMC): email@example.com
- Dr. Aldo Jongejan (Bioinformatics Laboratory, Amsterdam UMC, location AMC): firstname.lastname@example.org
- Prof. dr. Antoine van Kampen (Bioinformatics Laboratory, Amsterdam UMC, location AMC): email@example.com
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
|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)|
|13.30-16.30||Computer lab||Tutorial genome browsers||Aldo Jongejan||See below|
Tuesday, February 23, 2021
|10.00-12.00||Lecture||Statistical concepts for omics data analysis||Perry Moerland||Lecture (pptx)|
|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
|10.30-12.30||Lecture||Metabolomics||Antoine van Kampen||Lecture (pptx)|
|13.30-16.30||Computer lab||Metabolomics||Antoine van Kampen, Eric Wever, Mia Pras-Raves, Adrie Dane||See below|
Thursday, February 25, 2021
|10.00-12.00||Lecture||Pathways and networks||Perry Moerland||Lecture (pptx)|
|13.00-16.00||Computer lab||Pathways and networks||Perry Moerland||See below|
Friday, February 26, 2021
|10.00-12.00||Lecture||Genetical genomics||Perry Moerland||Lecture (pptx)|
|13.00-14.00||Lecture||Capita selecta||Perry Moerland||Lecture (zip)|
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
- Tutorial (pdf) (pdf with answers)
- TCGA Data (zipped)
- Papers (pdf): (Di Cello, 2013; Rosenbloom, 2015; Cunningham, 2015)
- TCGA Assembler (zip)
- BED files (zip)
- Human methylation BeadChip annotation (zip)
- Ensembl genome browser
- UCSC genome browser
- The Cancer Genome Atlas (TCGA)
- Infinium HumanMethylation450 BeadChip annotation
- Displaying your own data in UCSC
- UCSC data file formats (e.g., BED, bedGRAPH)
- Information about track line (in e.g., BED file)
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
Thursday, February 25: Pathways and networks
- 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.