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A Robust Model-free Approach for Rare Variants Association Studies Incorporating Gene-Gene and Gene-Environmental Interactions

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  • Ruixue Fan
  • Shaw-Hwa Lo

Abstract

Recently more and more evidence suggest that rare variants with much lower minor allele frequencies play significant roles in disease etiology. Advances in next-generation sequencing technologies will lead to many more rare variants association studies. Several statistical methods have been proposed to assess the effect of rare variants by aggregating information from multiple loci across a genetic region and testing the association between the phenotype and aggregated genotype. One limitation of existing methods is that they only look into the marginal effects of rare variants but do not systematically take into account effects due to interactions among rare variants and between rare variants and environmental factors. In this article, we propose the summation of partition approach (SPA), a robust model-free method that is designed specifically for detecting both marginal effects and effects due to gene-gene (G×G) and gene-environmental (G×E) interactions for rare variants association studies. SPA has three advantages. First, it accounts for the interaction information and gains considerable power in the presence of unknown and complicated G×G or G×E interactions. Secondly, it does not sacrifice the marginal detection power; in the situation when rare variants only have marginal effects it is comparable with the most competitive method in current literature. Thirdly, it is easy to extend and can incorporate more complex interactions; other practitioners and scientists can tailor the procedure to fit their own study friendly. Our simulation studies show that SPA is considerably more powerful than many existing methods in the presence of G×G and G×E interactions.

Suggested Citation

  • Ruixue Fan & Shaw-Hwa Lo, 2013. "A Robust Model-free Approach for Rare Variants Association Studies Incorporating Gene-Gene and Gene-Environmental Interactions," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-14, December.
  • Handle: RePEc:plo:pone00:0083057
    DOI: 10.1371/journal.pone.0083057
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    References listed on IDEAS

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    1. Benjamin M Neale & Manuel A Rivas & Benjamin F Voight & David Altshuler & Bernie Devlin & Marju Orho-Melander & Sekar Kathiresan & Shaun M Purcell & Kathryn Roeder & Mark J Daly, 2011. "Testing for an Unusual Distribution of Rare Variants," PLOS Genetics, Public Library of Science, vol. 7(3), pages 1-8, March.
    2. Bo Eskerod Madsen & Sharon R Browning, 2009. "A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic," PLOS Genetics, Public Library of Science, vol. 5(2), pages 1-11, February.
    3. Robert Makowsky & Nicholas M Pajewski & Yann C Klimentidis & Ana I Vazquez & Christine W Duarte & David B Allison & Gustavo de los Campos, 2011. "Beyond Missing Heritability: Prediction of Complex Traits," PLOS Genetics, Public Library of Science, vol. 7(4), pages 1-9, April.
    4. Brendan Maher, 2008. "Personal genomes: The case of the missing heritability," Nature, Nature, vol. 456(7218), pages 18-21, November.
    5. Teri A. Manolio & Francis S. Collins & Nancy J. Cox & David B. Goldstein & Lucia A. Hindorff & David J. Hunter & Mark I. McCarthy & Erin M. Ramos & Lon R. Cardon & Aravinda Chakravarti & Judy H. Cho &, 2009. "Finding the missing heritability of complex diseases," Nature, Nature, vol. 461(7265), pages 747-753, October.
    6. Iuliana Ionita-Laza & Joseph D Buxbaum & Nan M Laird & Christoph Lange, 2011. "A New Testing Strategy to Identify Rare Variants with Either Risk or Protective Effect on Disease," PLOS Genetics, Public Library of Science, vol. 7(2), pages 1-6, February.
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