Data analysis

Although data analysis only happens after the wet-lab experimental procedures are performed, it is a very important aspect of the design of all functional genomics experiments and should be considered before embarking on the wet-lab procedures. This is especially true for RNA-seq experiments (9, 10, RNAseqlopedia: Experimental Design).

Some important things to consider while planning your experiment are:

• How are you going to analyse your data?
• Is special software required? Is it free or does it need a licence?
• Is extra information needed? For example, a reference genome for aligning RNA-seq reads?
• Is bioinformatics expertise required? For example, if you’re expecting thousands of raw data files, each being several gigabytes in size, you will need some programmatic skills to manage them (open, copy, move, etc.).
• What are the hardware (storage and computational processing) requirements?
• What are the most appropriate statistical tests and has the experiment been designed so that you can use them?

Methods for analysing functional genomics data are discussed in the second part of this course ‘Functional genomics (II): Common technologies and data analysis methods‘.