Consistency of predictive signature genes and classifiers generated using different microarray platforms

Pharmacogenomics J. 2010 Aug;10(4):247-57. doi: 10.1038/tpj.2010.34.


Microarray-based classifiers and associated signature genes generated from various platforms are abundantly reported in the literature; however, the utility of the classifiers and signature genes in cross-platform prediction applications remains largely uncertain. As part of the MicroArray Quality Control Phase II (MAQC-II) project, we show in this study 80-90% cross-platform prediction consistency using a large toxicogenomics data set by illustrating that: (1) the signature genes of a classifier generated from one platform can be directly applied to another platform to develop a predictive classifier; (2) a classifier developed using data generated from one platform can accurately predict samples that were profiled using a different platform. The results suggest the potential utility of using published signature genes in cross-platform applications and the possible adoption of the published classifiers for a variety of applications. The study reveals an opportunity for possible translation of biomarkers identified using microarrays to clinically validated non-array gene expression assays.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • DNA Probes
  • Databases, Genetic
  • Gene Expression Profiling
  • Genes*
  • Humans
  • Oligonucleotide Array Sequence Analysis / methods*
  • Pharmacogenetics / methods*
  • Phenotype
  • Predictive Value of Tests
  • Quality Control
  • Toxicogenetics / methods*


  • DNA Probes