Gene expression data analysis using R: How to make sense out of your RNA-Seq/microarray data

Course date: 14 October 2019 - 18 October 2019
Location: Erasmus MC, COO-3+OWR-31

Click here for details of programme
Click here to register for this course

Please find all the files in a public dropbox:


Gene Expression data analysis using R: How to make sense out of you RNA-Seq/microarray data

Five days hands-on computer course focuses on microarray and next-generation sequencing gene expression data, but some concepts may be applicable to other types of genomics data. Most of the speakers (and therefore examples) have a biomedical background. Software packages used are freeware, including the statistical software R, Bioconductor, Cytoscape and web tools. 
Knowlegde of R required
For those of you who have no knowledge of R, it is required to work your way through the attached introduction in R. It is necessary to do so, because in this course we will not cover the basics of R but assume that you already have this basic knowledge.

Under abstracts/reviews in preparation of the course you will find a .zip file that contains: 
- instructions on how to install R
- exercises for R

Learning objectives
1. The participant has insight in the issues involved in good experimental design, including power to detect differential expression in microarray and next-generation sequencing data.
2. The participant knows and can perform analysis steps in expression data analysis, visually present and judge the results for:
· quality control and preprocessing,
· finding differentially expressed genes, 
· cluster analysis, 
· classification analysis,
· pathway testing.
3. The participant has insight in the different algorithms and options available to perform an analysis, and can make an informed choice.
4. The participant knows the pitfalls of existing analyses and is able to critically judge the statistical analysis of expression data performed by others.

Pre-requisites for participants
Participants need to know what a microarray experiment and RNA sequencing is, and have their own expression profiling data. They have preferably followed an introduction to R course; alternatively they have practiced the "Getting started in R" practical prior to the course. Basic statistical concepts including mean, variance, standard deviation, probability distributions, t-test, p-value, correlation, and linear regression are assumed known. These are typically seen during basic statistics courses.

The course is intensive, and covers the basic concepts and methods required for expression data analysis. Presentations are followed by hands-on computer sessions to directly apply and get more insight in the analysis methods. One afternoon is dedicated to the analysis of a new data set, allowing the students to refresh and extend their analysis skill. After the course, the presentations, practicals and test data will remain available for future reference. Software packages used are freeware, including the statistical software R, Bioconductor, Cytoscape and web tools. 

Course material from previous courses 

Here you can find the website with course material about R:

Please fill in the online registration form (in the free text box at the bottom of the form):

• do you have basis R knowledge (yes/no); if yes, please indicate how you acquired this knowledge: basic R course/ other…;
• do you have gene expression data to analyse yes/no, if yes: which platform? Affymetrix/ Illumina microarrays/ Agilent/ other: .....

Audience and participation
For biological and clinical researchers whose research involves experiments that generate gene expression data. 

Teacher/Speakers/ Organisation
Judith Boer, Princess Máxima Center for Pediatric Oncology, Utrecht
Marcel Reinders, Information and Communication Theory Group, TU Delft
Renée de Menezes, Department of Epidemiology and Biostatistics, VuMC, Amsterdam
Harmen vd Werken/ Job van Riet, Cancer Computational Biology Center (CCBC) and Department of Urology, Erasmus MC
Mitra Ebrahimpoor, department of Biostatistics, LUMC 
Andrew Stubbs and Willem de Koning, Department of Pathology, Erasmus MC
Martina Kutmon, BiGCaT, Maastricht University
Peter van Baarlen, Host-Microbe Interactomics Group, Animal Sciences, Wageningen University
Course organizers
Dr.Ir. Harmen van de Werken and Dr. Andrew Stubbs
Dr. Silvie Hansenova Manaskova and Dr. Frank van Vliet, Managing Director MolMed, 010-70 43518/ 06-5474 6408,

Date, Time & Location
14 October 09.00 - 17.00 COO-3
15 October 08.45 - 10.45 OWR-31, 10.45-17.00 COO-3 
16 October 08.45 - 17.00 COO-3
17 October 08.45 - 15.15 COO-3, 15.15-17.15 Ee-15.28
18 October 08.45 - 16.00 COO-3

Full participation is  2,0 ECTS.


Course fees 
For non-commercial participants the course fee  €700/5 days
PhD students get a 50% discount and pay €350/ 5 days. 
Participants from the postgraduate school MolMed get a 100% discount and pay €0.
Master students, get a 50% discount and pay €350/ 5 days. 
Master students who have to pay the fee from their personal budget get a 75% discount and pay €175/5 days. 
If these financial requirements should pose a problem, please contact Frank van Vliet, managing director of the Erasmus Postgraduate School Mol Med, at:

General information
Financial regulation of the Postgraduate School MolMed, from January 1st 2019, the following financial rules apply, but they may differ per course still. Look at the course fee of each course to be sure which discounts are really applied:
• Non-commercial course, symposium or workshop fee: €200/day, €700/week
• Participants of the postgraduate school MolMed: discount of 100%
• However, the Personal Leadership course and the workshops Photoshop/Illustrator/Indesign have to be paid from the ‘personal budget’ of employees, MolMed members and PhD students included. So they will receive an invoice from us which you have to pay and which will be reimbursed by your Department. When you will pay from your personal budget you need to provide us your home address details for the invoice. 
If there is no personal budget left, the MM-members get a discount of 100%.
• PhD students and Master’s students, regardless of institution: discount of 50%.
•The course fees of research master’s students will be paid by their master program at rate of €100/ECTS. For not I&I master students: please inform your master program in advance whether they agree to pay.
•Master’s students who are paying the fee from their private budget: discount of 75%. When you will pay from your personal budget you need to provide us your home address details for the invoice.
•However, 2 courses in statistics are paid centrally by the Dept. of Research policy for all PhD students from Erasmus MC! These are R and the SPSS course. So for Erasmus MC PhD students, these courses are always free, provided you are officially registered as a PhD student.
There is one fee for the entire course. There is no reduction for partial participation.
Commercial participants, companies & sponsors are invited to inquire about commercial tuition fees and about sponsoring.
All invoices will be sent by email to the mail address that you filled in upon registration. If this address is not correct we use your Erasmus MC address.

Those who register for a course, symposium or workshop agree with these financial conditions.


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