On Sunday, Sept. 16, 2012, Nature Genetics published the paper "Rapid variance components–based method for whole-genome association analysis" by Svisheva, Belonogova, Axenovich, van Duijn and Aulchenko.
The authors present an extremely fast variance components–based two-step method, GRAMMAR-Gamma, developed as an analytical approximation within a framework of the score test approach. Using simulated and real human GWAS data sets, we show that this method provides unbiased estimates of the SNP effect and has a power close to that of the likelihood ratio test–based method. At the same time, the computational complexity of the method is close to its theoretical minimum, that is, to the complexity of the analysis that ignores genetic structure. The running time of the method linearly depends on sample size, whereas this dependency is quadratic for other existing methods. Simulations suggest that GRAMMAR-Gamma may be used for association testing in whole-genome resequencing studies of large human cohorts.
Grammar-Gamma method is available as a part of "grammar" function of the GenABEL package. For the moment, it is included in the development version, but will be released on CRAN in GenABEL v 1.7-2 in few days.