Normalisation of microarray data is used to control for technical variation between assays, while preserving the biological variation (4). There are many ways to normalise the data, and the methods used depend on:

  • the type of array
  • the design of the experiment
  • assumptions made about the data (e.g. ‘the majority of genes represented on the microarray are not expected to be differentially expressed in the test group relative to controls’)
  • and the package being used to analyse the data

For Expression Atlas, Affymetrix microarray data is normalised using the ‘Robust Multi-Array Average’ (RMA) method within the ‘oligo’ package.

Agilent microarray data is normalised using the ‘limma’ package: ‘quantile normalisation’ for one-colour microarray data.

For a detailed discussion of normalisation methods see Grant et al. 2007 (4).