Journal
AMERICAN JOURNAL OF HUMAN GENETICS
Volume 78, Issue 5, Pages 884-888Publisher
CELL PRESS
DOI: 10.1086/503751
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Funding
- NCI NIH HHS [R01 CA088164, CA88164, CA94211, R01 CA094211] Funding Source: Medline
- NIGMS NIH HHS [GM061390, U19 GM061390, U01 GM061390] Funding Source: Medline
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The ability of genomewide association studies to decipher genetic traits is driven in part by how well the measured single-nucleotide polymorphisms cover the unmeasured causal variants. Estimates of coverage based on standard linkage-disequilibrium measures, such as the average maximum squared correlation coefficient (r(2)), can lead to inaccurate and inflated estimates of the power of genomewide association studies. In contrast, use of the cumulative r(2) adjusted power measure presented here gives more-accurate estimates of power for genomewide association studies.
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