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Pathway Analysis of the Human Brain Transcriptome in Disease

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Abstract

Pathway analysis is a powerful method for discerning differentially regulated genes and elucidating their biological importance. It allows for the identification of perturbed or aberrantly expressed genes within a biological context from extensive data sets and offers a simplistic approach for interrogating such data sets. With the growing use of microarrays and RNA-Seq, data for genome-wide studies are growing at an alarming rate, and the use of deep sequencing is revealing elements of the genome previously uncharacterised. Through the employment of pathway analysis, mechanisms in complex diseases may be explored and novel causatives found primarily through differentially regulated genes. Further, with the implementation of next generation sequencing, a deeper resolution may be attained, particularly in identification of isoform diversity and SNPs. Here, we look at a broad overview of pathway analysis in the human brain transcriptome and its relevance in teasing out underlying causes of complex diseases. We will outline processes in data gathering and analysis of particular diseases in which these approaches have been successful.

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Acknowledgments

This work was supported by the National Health and Medical Research Council of Australia (1022325 to WSK, 630434 to GMH).

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Authors and Affiliations

  1. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, 2052, Australia

    Tomas Kavanagh, James D. Mills & Michael Janitz

  2. Neuroscience Research Australia, Sydney, New South Wales, 2031, Australia

    Woojin S. Kim & Glenda M. Halliday

  3. School of Medical Sciences, University of New South Wales, Sydney, New South Wales, 2052, Australia

    Woojin S. Kim & Glenda M. Halliday

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  1. Tomas Kavanagh
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  2. James D. Mills
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  3. Woojin S. Kim
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Correspondence to Michael Janitz.

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Kavanagh, T., Mills, J.D., Kim, W.S. et al. Pathway Analysis of the Human Brain Transcriptome in Disease. J Mol Neurosci 51, 28–36 (2013). https://doi.org/10.1007/s12031-012-9940-0

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