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From patterns to pathways: gene expression data analysis comes of age

Nature Genetics volume 32, pages 502–508 (2002)Cite this article

Abstract

Many different biological questions are routinely studied using transcriptional profiling on microarrays. A wide range of approaches are available for gleaning insights from the data obtained from such experiments. The appropriate choice of data-analysis technique depends both on the data and on the goals of the experiment. This review summarizes some of the common themes in microarray data analysis, including detection of differential expression, clustering, and predicting sample characteristics. Several approaches to each problem, and their relative merits, are discussed and key areas for additional research highlighted.

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Figure 1: The advantage of permutation-based adjustment for multiple testing.
Figure 2: Two pattern-discovery techniques.
Figure 3: An overview of the process for building a prediction model to classify samples.

Katie Ris

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Acknowledgements

I thank Gene Brown, Lenore Cowen, Steve Haney, Andrew Hill, Steve Rozen and Timm Triplett for helpful discussions and comments.

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  1. Department of Genomics, Wyeth Research, 35 Cambridge Park Drive, Cambridge, 02140, Massachusetts, USA

    Donna K. Slonim

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Slonim, D. From patterns to pathways: gene expression data analysis comes of age. Nat Genet 32 (Suppl 4), 502–508 (2002). https://doi.org/10.1038/ng1033

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