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Genome Data Analysis pp 79–93Cite as

Advanced Microarray Data Analysis

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Abstract

In this chapter, we provide a basic understanding of microarray data analysis, which is the foundation of gene expression data analysis. This chapter describes a microarray experiment method and the data structure generated by microarray. There are exercises to identify differentially expressed genes between case and control groups, to perform cluster and classification analysis, and to understand the importance of biological pathway analysis with the interpretation of microarray data using the GSEA program and R package.

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Notes

  1. 1.

    ► https://www.ncbi.nlm.nih.gov/geo/

  2. 2.

    ► https://www.ebi.ac.uk/arrayexpress/

  3. 3.

    ► https://www.oncomine.org/

  4. 4.

    In the dyeing method, reverse transcription (RT) transforms mRNA into complementary single-strand cDNA using oligo-dTprimer and reverse transcriptase for technical convenience. In this case, Cy3-dUTP, which emits green light, and Cy5-dUTP, which emits red light, are added into each reaction separately, which converts all mRNA in the reference and test cell to target cDNA by mixing Cy3 and Cy5.

  5. 5.

    Instead of using absolute light intensity, the relative value of the opening of the aperture or the sensitivity setting of the light sensor is used.

  6. 6.

    Often, rRNAand GAPDH (glyceraldehyde 3-phosphate dehydrogenase) are used.

  7. 7.

    Dye bias is dependent on spot intensity.

  8. 8.

    ► http://cybert.ics.uci.edu

  9. 9.

    FWER = Pr(α > 0).

  10. 10.

    pFDR = E(α / rejected | rejected >0).

  11. 11.

    Molecular Signature Database, ► http://software.broadinstitute.org/gsea/msigdb/

  12. 12.

    S(t) is survival function.

  13. 13.

    Prognostic subgroup prediction.

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Authors and Affiliations

  1. Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, South Korea

    Ju Han Kim

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  1. Ju Han Kim
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Kim, J.H. (2019). Advanced Microarray Data Analysis. In: Genome Data Analysis. Learning Materials in Biosciences. Springer, Singapore. https://doi.org/10.1007/978-981-13-1942-6_5

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