Statistical considerations for analysis of microarray experiments

Clin Transl Sci. 2011 Dec;4(6):466-77. doi: 10.1111/j.1752-8062.2011.00309.x. Epub 2011 Nov 7.


Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generates a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Algorithms
  • Clinical Trials as Topic
  • Computational Biology / methods*
  • Gene Expression Profiling*
  • Gene Expression Regulation, Leukemic
  • Gene Expression Regulation, Neoplastic
  • Genetic Markers / genetics
  • Humans
  • Leukemia / metabolism
  • Lung Neoplasms / diagnosis
  • Lung Neoplasms / metabolism
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis / methods*
  • Phenotype
  • Prognosis
  • Software


  • Genetic Markers