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Bioinformatics Challenges in Genome-Wide Association Studies (GWAS)

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Clinical Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1168))

Abstract

Genome-wide association studies (GWAS) are a powerful tool for investigators to examine the human genome to detect genetic risk factors, reveal the genetic architecture of diseases and open up new opportunities for treatment and prevention. However, despite its successes, GWAS have not been able to identify genetic loci that are effective classifiers of disease, limiting their value for genetic testing. This chapter highlights the challenges that lie ahead for GWAS in better identifying disease risk predictors, and how we may address them. In this regard, we review basic concepts regarding GWAS, the technologies used for capturing genetic variation, the missing heritability problem, the need for efficient study design especially for replication efforts, reducing the bias introduced into a dataset, and how to utilize new resources available, such as electronic medical records. We also look to what lies ahead for the field, and the approaches that can be taken to realize the full potential of GWAS.

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Abbreviations

EMR:

Electronic medical record

GWAS:

Genome-wide association study/studies

LD:

Linkage disequilibrium

MAF:

Minor allele frequency

SNP:

Single nucleotide polymorphism

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Author information

Authors and Affiliations

  1. Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA

    Rishika De & Jason H. Moore

  2. Department of Biomedical Informatics, Center for Human Genetics Research, Vanderbilt University Medical School, Nashville, TN, USA

    William S. Bush

  3. Department of Genetics, Dartmouth-Hitchcock Medical Center, Geisel School of Medicine, HB7937 One Medical Center Dr., Lebanon, NH, 03756, USA

    Jason H. Moore

Authors
  1. Rishika De
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  2. William S. Bush
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  3. Jason H. Moore
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Corresponding author

Correspondence to Jason H. Moore .

Editor information

Editors and Affiliations

  1. Department of Medical Genomics, Royal Prince Alfred Hospital and Sydney Medical School, University of Sydney, Camperdown, Australia

    Ronald Trent

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De, R., Bush, W.S., Moore, J.H. (2014). Bioinformatics Challenges in Genome-Wide Association Studies (GWAS). In: Trent, R. (eds) Clinical Bioinformatics. Methods in Molecular Biology, vol 1168. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0847-9_5

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  • DOI: https://doi.org/10.1007/978-1-4939-0847-9_5

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0846-2

  • Online ISBN: 978-1-4939-0847-9

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