Bring Your Own Data: R-coding for analysing RNA-seq data (2023-I)

Course description

Obtaining results from RNA-seq data requires appropriate statistics and is presented in figures. A combination of large data sets, performing the right statistics, the multitude of analysis options and being able to code can make this a challenge. With this course we offer you the opportunity to Bring Your Own Data (BYOD) to learn how to obtain results from processed RNA-seq data (count tables) using R. All hands-on and under the supervision of experienced trainers. At the end of the course, you will have analysed your data set and generated a figure of your analysis results.

A basic understanding of R and R-studio is required. If you do not have this yet, consider to take the course Introduction to R for Life Sciences first. In addition, the course will be easier to follow with some knowledge of the R package ggplot2. If you do not have this yet, consider taking the course Bring your Own Data: create figures in R using ggplot2.

Note: Please bring processed data ready to be analysed. Raw sequence data is not suitable for this course. Please generate count tables first. If you are in doubt feel free to contact the trainer.

Important: for this course you need to bring your own laptop.

Learning objectives

• Become aware of the analysis steps needed to analyse RNA-seq data.
• Become aware of the choices you can make when analysing RNA-seq data and why they matter.
• Perform the correct statistics using R coding.
• Make figures to visualise your data in order to interpret the data.
• Make high-quality, near publication ready figures, using the R package ggplot2 
• Learn the different possibilities for visualisation of your RNA-seq data using ggplot2.

Instructional method

For this course you will work on your own laptop. One week before the course starts you receive an email with instructions on how to install the software. We also ask you to inform us which dataset you would like to bring. The course will be a combination of in-class lectures, hands-on questions and answers sessions and working on your own data. At the end of the course, you will shortly present and discuss one of the figures you have made during the course to show your progress.

Trainer

You will be trained by one of the professionals of Utrecht Bioinformatics Center, Utrecht University.

Group size            

12 to 20 participants

Number of credits                                 

1.5 EC

Course schedule

Study load

In addition to the scheduled sessions, you should consider an extra study load of approximately 4 hours in total. This study load mostly consists of applying the learned skills on your own data to prepare questions for the next session.

Course certificate                                

You will receive a course certificate after actively participating in all course sessions, including presenting and discussing one of the figures you have made.

Cancellation and No-show policy

This course is free for GSLS PhD candidates. However: free of charge does not mean free of responsibility. Once you have signed up for a course, we expect you to attend. For every late cancellation or no-show we have had to disappoint others who would have liked to attend. This is our policy:

• You may cancel free of charge up to 4 weeks before the start of the course. After this date you can only cancel if you have a GSLS PhD candidate to replace you in the course. Send the name and contact information of your replacement to pcc@uu.nl, at least 2 working days before the start of the course;
• We expect that you actively attend the full course, but at least 80%. It is mandatory to attend the first session. If you are absent the first session you cannot follow the remaining of the course;
• Not meeting the above requirements means you will be charged a no-show fee (€ 75). We will send the invoice after the course has ended. We are unable to make any exceptions, unless you have a valid reason (i.e., illness or death in the family 1^st/2^nd degree or partner). Your supervisor has to send an e-mail to pcc@uu.nl indicating the reason.

Unfortunately we don’t offer this course for participants not part of the GSLS. Our courses tend to be fully booked by GSLS PhD candidates.