4.5 Article

EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units

Journal

EUROPEAN JOURNAL OF HUMAN GENETICS
Volume 19, Issue 4, Pages 465-471

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/ejhg.2010.196

Keywords

Epistasis; genome-wide interaction analysis; graphical processing unit

Funding

  1. Max Planck Society
  2. German ministry for Education and Research (BMBF) through the NGFN [Moods-01GS08145]
  3. German Competence Network Multiple Sclerosis (KKNMS)
  4. MEXT Kakenhi [21680025]
  5. FIRST program
  6. Grants-in-Aid for Scientific Research [21680025] Funding Source: KAKEN
  7. Medical Research Council [G9817803B] Funding Source: researchfish

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Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case-control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair. European Journal of Human Genetics (2011) 19, 465-471; doi:10.1038/ejhg.2010.196; published online 8 December 2010

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