Application of z-score transformation to Affymetrix data.

Chris Cheadle, Yoon S. Cho-Chung, Kevin G. Becker, Marquis P. Vawter

Research output: Contribution to journalArticlepeer-review

70 Scopus citations


Z-score transformation has been successfully used as a normalisation procedure for microarray data generated using radioactively labelled probes with spotted cDNA arrays. One of the advantages of the z-score transformation method is that it provides a way of standardising data across a wide range of experiments and allows the comparison of microarray data independent of the original hybridisation intensities. The feasibility of applying z-score transformation to other types of linear microarray data, specifically that generated using fluorescently labelled probes with Affymetrix chips, was tested in three separate scenarios and is discussed here. In the first scenario, Affymetrix data from the NCBI (National Center for Biotechnology Information) GEO (Gene Expression Omnibus) database was used to demonstrate that z-score transformation preserved the essential phylogenetic grouping between primate species' fibroblast gene expression baseline measurements. The second scenario employed z-score transformation on data consisting of a series of genes spiked-in at known concentrations and arrayed in a Latin square format. We were able to reconstruct the entire set of spike-in concentration curves without prior knowledge of their format by using z-score transformation as the normalisation process. Finally, we show that z-score transformed data maintains the integrity of separate samples from different experiments and laboratories, as demonstrated by accurate grouping of clustered data according to sample identity. We conclude that data normalised by z-score transformation can be easily used with Affymetrix data without noticeable loss of information content. Z-score transformation provides a useful tool for comparisons between experiments and between laboratories that use the Affymetrix platform.

Original languageEnglish (US)
Pages (from-to)209-217
Number of pages9
JournalApplied bioinformatics
Issue number4
StatePublished - 2003
Externally publishedYes

ASJC Scopus subject areas

  • Information Systems
  • Agricultural and Biological Sciences(all)
  • Computer Science Applications


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