When analysing sequencing data, you should always start with a quality control step to clean your data and make sure your data is good enough to answer your research question. After this step, you will often proceed with a mapping (alignment) or genome assembly step, depending on whether you have a reference genome to work with.

Time estimation: 30 minutes

Learning objectives:

• To understand the pitfalls in scRNA-seq sequencing and amplification, and how they are overcome.
• Know the types of variation in an analysis and how to control for them.
• Grasp what dimension reduction is, and how it might be performed.
• Be familiarised with the main types of clustering techniques and when to use them.