Call for Papers
Focus Theme: “Chronic disease registries – trends and challenges”
Deadline: Sept 1, 2016

Call for Papers
Focus Theme: „Single Subject Research Design and Data Processing“
Deadline: Nov 1, 2016

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Archive (2005–1962)

Multiplicity Issues in Microarray Experiments

Journal: Methods Archive
ISSN: 0026-1270
Issue: 2005 (Vol. 44): Issue 3 2005
Pages: 431-437

Multiplicity Issues in Microarray Experiments

F. Bretz1 , J. Landgrebe2 , E. Brunner3

1 B&SR, Novartis Pharma AG, Basel, Switzerland 2 Abteilung Biochemie II, Universität Göttingen, Göttingen, Germany 3 Abteilung Medizinische Statistik, Universität Göttingen, Göttingen, Germany


Screening, Familywise error rate, false discovery rate, error concepts


Objectives: Discussion of different error concepts relevant to microarray experiments. Review of some commonly used multiple testing procedures. Comparison of different approaches as applied to gene expression data. Methods: This article focuses on familywise error rate (FWER) and false discovery rate (FDR) controlling procedures. Methods under investigation include: Bonferroni-type methods and their improvements (including resampling approaches), modified Bonferroni methods, data-driven approaches, as well as the linear step-up method and its modifications. Particular emphasis lies on the description of the assumptions, advantages and limitations for the investigated methods. Results: FWER controlling procedures are often too conservative in high dimensional screening studies. A better balance between the raw P -values and the stringent FWER-adjusted P -values may be required in many situations, as provided by FDR controlling and related procedures. Conclusions: The questions remain open, which error concept to apply and which multiple testing procedure to use. Although we believe that the FDR or one of its variants will be applied more often in the future, longterm experience with microarray technology is missing and thus the validity of appropriate multiple test procedures cannot yet be assessed for microarray data analysis.

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