Experimental structure

A lot of the difficulties in analysis and/ or workflows come from the complexities of experimental structure. A lot of terms are used interchangeably in different contexts. Most tools for untargeted metabolomics are set up for 1 factor analysis with two or three levels e.g.

  • case vs control
  • wild-type vs transgenic line
  • Strain 1 vs strain 2 vs strain 3

However, we quite often have more complex experimental designs when coming from other fields e.g.

  • 2 factor with two or more levels in each such as +/- treatment for 2 strains
  • Time course for 1 or 2 factors such as +/- treatment for 2 strains over three time points

⚠️ Before you start, think about the following questions and make a note of what you’re expecting in terms of which groups of metabolite fingerprints could be similar and which could be different to each other.

I don’t mean hypothesise but more, think logically about what you’re asking in your analysis and how your data will be grouped.

  • What are your biological replicates and are they independent of each other (or have you resampled the same organism/ population multiple times)?
  • Do you have technical replicates (was each extract run through the MS multiple times)?
  • Do you want/ need any QC samples, or analytical standard samples?
  • What groupings do you need to use to ask the questions you want answers to?

💡 Get your meta-data (e.g. treatment information) organised early.