4.7 Review

Statistical analysis strategies for association studies involving rare variants

Journal

NATURE REVIEWS GENETICS
Volume 11, Issue 11, Pages 773-785

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/nrg2867

Keywords

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Funding

  1. Price Foundation
  2. Scripps Genomic Medicine
  3. Charles University [GAUK 134,609]
  4. Scripps Translational Science Institute
  5. [U19 AG023122-05]
  6. [R01 MH078151-03]
  7. [N01 MH22005]
  8. [U01 DA024417-01]
  9. [P50 MH081755-01]
  10. [R01 AG030474-02]
  11. [N01 MH022005]
  12. [R01 HL089655-02]
  13. [R01 MH080134-03]
  14. [U54 CA143906-01]
  15. [UL1 RR025774-03]

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The limitations of genome-wide association (GWA) studies that focus on the phenotypic influence of common genetic variants have motivated human geneticists to consider the contribution of rare variants to phenotypic expression. The increasing availability of high-throughput sequencing technologies has enabled studies of rare variants but these methods will not be sufficient for their success as appropriate analytical methods are also needed. We consider data analysis approaches to testing associations between a phenotype and collections of rare variants in a defined genomic region or set of regions. Ultimately, although a wide variety of analytical approaches exist, more work is needed to refine them and determine their properties and power in different contexts.

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