Description Usage Arguments Details Value Author(s) References See Also Examples

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

1 | ```
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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
## 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)
``` |

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