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Analysis of Global Gene Expression Profiles

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Book cover Multiple Myeloma

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1792))

Abstract

DNA microarrays have considerably helped to improve the understanding of biological processes and diseases including multiple myeloma (MM). GEP analyses have been successful to classify MM, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance.

This generated large amounts of publicly available data that could benefit from easy-to-use bioinformatics resources to analyze them. Here we present easy-to-use and open-access bioinformatics tools to extract and visualize the most prominent information from GEP data.

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Acknowledgments

This work was supported by grants from French INCA (Institut National du Cancer) Institute (PLBIO15-256) and ITMO Cancer (MM&TT).

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Authors and Affiliations

  1. Department of Biological Hematology, CHU Montpellier, Montpellier, France

    Alboukadel Kassambara & Jerome Moreaux

  2. Institute of Human Genetics, UMR 9002, CNRS and University of Montpellier, Montpellier, France

    Alboukadel Kassambara & Jerome Moreaux

  3. UFR de Médecine, University of Montpellier, Montpellier, France

    Jerome Moreaux

  4. Department of Biological Hematology, Laboratory for Monitoring Innovative Therapies, Hopital Saint-Eloi—CHRU de Montpellier, Montpellier, France

    Jerome Moreaux

Authors
  1. Alboukadel Kassambara
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  2. Jerome Moreaux
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Correspondence to Jerome Moreaux .

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Editors and Affiliations

  1. Janssen R&D, Spring House, PA, USA

    Christoph Heuck

  2. The Myeloma Institute, University of Arkansas for Medical Science, Little Rock, AR, USA

    Niels Weinhold

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Kassambara, A., Moreaux, J. (2018). Analysis of Global Gene Expression Profiles. In: Heuck, C., Weinhold, N. (eds) Multiple Myeloma. Methods in Molecular Biology, vol 1792. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-7865-6_11

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  • DOI: https://doi.org/10.1007/978-1-4939-7865-6_11

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