WST {AssotesteR} | R Documentation |
The WST method has been proposed by Wang and Elston (2007) and it can be seen as a fixed effects method with transformed predictors based on Fourier Transformations. WST is based on Fourier Transform (FT) coefficients to globally test a set of correlated genetic variants (e.g. SNPs). The sequence of genetic variants values is transformed into a sequence of numbers by discrete FT, but only the real parts of the FT coefficients are taken into account. A weighted score statistic of the FT components is calculated, which follows a standard normal distribution under the null hypothesis
WST(y, X, perm = 100)
y |
numeric vector with phenotype status: 0=controls, 1=cases. No missing data allowed |
X |
numeric matrix or data frame with genotype data coded as 0, 1, 2. NO missing data is allowed |
perm |
positive integer indicating the number of permutations (100 by default) |
This function does not allow missing genotypes
An object of class "assoctest"
, basically a list with the following elements:
wst.stat |
wst statistic |
asym.pval |
asymptotic p-value |
perm.pval |
permuted p-value |
args |
descriptive information with number of controls, cases, variants, and permutations |
name |
name of the statistic |
Gaston Sanchez
Wang T, Elston C (2007) Improved Power by Use of a Weighted Score Test for Linkage Disequilibrium Mapping. The American Journal of Human Genetics, 80: 353-360
## Not run: # number of cases cases = 500 # number of controls controls = 500 # total (cases + controls) total = cases + controls # phenotype vector phenotype = c(rep(1, cases), rep(0, controls)) # genotype matrix with 10 variants (random data) set.seed(123) genotype = matrix(rbinom(total*10, 2, 0.05), nrow=total, ncol=10) # apply WST with 500 permutations mywst = WST(phenotype, genotype, perm=500) mywst ## End(Not run)