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Analysis of Population-Based Genetic Association Studies Applied to Cancer Susceptibility and Prognosis

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Abstract

Along hundreds of thousands of years, genetic variation has been the keystone for human evolution and adaptation to the surrounding environment. Although this fact has supposed a great progress for the species, mutations in our DNA sequence may also lead to an increased risk of developing some diseases with an underlying genetic basis, such as cancer. Among different genetic epidemiology branches, population-based association studies are one of the tools that can help us decipher which of these mutations are involved in the appearance or progression of the disease. This chapter aims to be a didactic but thorough review for those who are interested in genetic association studies and its analytical methodology. It will mainly focus on SNP-array analysis techniques, covering issues such as quality control, assessment of association with disease, gene–gene and gene–environment interactions, haplotype analysis, and genome-wide association studies. In the last part, some of the existing bioinformatics tools that perform the exposed analyses will be reviewed.

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Authors and Affiliations

  1. Biostatistics and Bioinformatics Unit, Catalan Institute of Oncology – IDIBELL, Av. Gran Via s/n Km 2.7, 08907 L’Hospitalet de Llobregat, Barcelona, Spain

    Xavier Solé

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  1. Xavier Solé
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  2. Juan Ramón González
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  3. Víctor Moreno
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Correspondence to Xavier Solé .

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  1. Discipline of Information Technology, James Cook University, Townsville, 4811, Australia

    Tuan Pham

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Solé, X., González, J.R., Moreno, V. (2009). Analysis of Population-Based Genetic Association Studies Applied to Cancer Susceptibility and Prognosis. In: Pham, T. (eds) Computational Biology. Applied Bioinformatics and Biostatistics in Cancer Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0811-7_7

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