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PubMed · 16802876

Some statistical issues in microarray gene expression data.

Matthew S Mayo·Byron J Gajewski·Jeffrey S Morris
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Abstract

In this paper we discuss some of the statistical issues that should be considered when conducting experiments involving microarray gene expression data. We discuss statistical issues related to preprocessing the data as well as the analysis of the data. Analysis of the data is discussed in three contexts: class comparison, class prediction and class discovery. We also review the methods used in two studies that are using microarray gene expression to assess the effect of exposure to radiofrequency (RF) fields on gene expression. Our intent is to provide a guide for radiation researchers when conducting studies involving microarray gene expression data.

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ArtifactsComputer SimulationData Interpretation, StatisticalGene Expression ProfilingModels, GeneticModels, StatisticalOligonucleotide Array Sequence AnalysisQuality ControlReproducibility of ResultsSensitivity and SpecificityJournal ArticleResearch Support, N.I.H., Extramural

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Matthew S Mayo, Byron J Gajewski, Jeffrey S Morris. 2006. Some statistical issues in microarray gene expression data.. https://doi.org/10.1667/rr3576.1

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