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RNA-Seq and Expression Arrays: Selection Guidelines for Genome-Wide Expression Profiling

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Gene Expression Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1783))

Abstract

The development of genome-wide gene expression profiling technologies over the past two decades has produced great opportunity for researchers to explore the transcriptome and to better understand biological systems and their perturbation. In this chapter we provide an overview of microarray and massively parallel sequencing technologies and their application to gene expression analysis. We discuss factors that impact expression data generation and analysis that which should be considered in the application of these technology platforms. We further present the results of a simple illustration study to highlight performance similarities and differences in expression profiling of protein-coding mRNAs with each platform. Based on technical and analytical differences between the two platforms, reports in the literature comparing arrays and RNA-Seq for gene expression, and our own example study and experience, we provide recommendations for platform selection for gene expression studies.

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Acknowledgments

The authors thank Julja Burchard for enthusiastic and thoughtful discussions on the design and content of the chapter. We thank Dr. Robert Searles for manuscript review and expert advice on RNA-Seq methods. We thank Caitlin Harrington-Smith for creative assistance with figures and Amy Carlos and Kristina Vartanian for excellent technical assistance. This work was supported in part by the OHSU Knight Cancer Institute (NIH NCI Cancer Center Support Grant P30 CA069533-17) and NIH/NCIR01CA169175 (to P. Schedin).

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Authors and Affiliations

  1. School of Public Health, Oregon Health and Science University, Portland, OR, USA

    Jessica Minnier

  2. Department of Cell, Developmental and Cancer Biology, Oregon Health and Science University, Portland, OR, USA

    Nathan D. Pennock & Qiuchen Guo

  3. Department of Cell, Developmental and Cancer Biology, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA

    Pepper Schedin

  4. Young Women’s Breast Cancer Translational Program, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

    Pepper Schedin

  5. Integrated Genomics Laboratory, Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA

    Christina A. Harrington

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  1. Jessica Minnier
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  2. Nathan D. Pennock
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  3. Qiuchen Guo
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  4. Pepper Schedin
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  5. Christina A. Harrington
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Correspondence to Christina A. Harrington .

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Editors and Affiliations

  1. Division of Geriatrics and Clinical Gerontology, National Institute on Aging, Bethesda, Maryland, USA

    Nalini Raghavachari

  2. Environmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, Mississippi, USA

    NatĂ lia Garcia-Reyero

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Minnier, J., Pennock, N.D., Guo, Q., Schedin, P., Harrington, C.A. (2018). RNA-Seq and Expression Arrays: Selection Guidelines for Genome-Wide Expression Profiling. In: Raghavachari, N., Garcia-Reyero, N. (eds) Gene Expression Analysis. Methods in Molecular Biology, vol 1783. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7834-2_2

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  • DOI: https://doi.org/10.1007/978-1-4939-7834-2_2

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