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PLoS Computational Biology
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PLoS Computational Biology
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PLoS Computational Biology
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Chapter 11: Genome-Wide Association Studies

Authors: William S Bush; Jason H Moore;

Chapter 11: Genome-Wide Association Studies

Abstract

Genome-wide association studies (GWAS) have evolved over the last ten years into a powerful tool for investigating the genetic architecture of human disease. In this work, we review the key concepts underlying GWAS, including the architecture of common diseases, the structure of common human genetic variation, technologies for capturing genetic information, study designs, and the statistical methods used for data analysis. We also look forward to the future beyond GWAS.

Related Organizations
Keywords

QH301-705.5, Genetic Linkage, Genetic Variation, Education, Phenotype, Haplotypes, Electronic Health Records, Humans, Biology (General), Genome-Wide Association Study

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
943
Top 0.1%
Top 1%
Top 0.1%
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gold