Description Usage Arguments Value Note Author(s) See Also Examples

The mean of a Wilcoxon statistic is unaffected by correlation within the variable under test, but its variance is. This function uses a set of Wilcoxon statistics generated from permuted data to estimate the variance empirically, and thus calculate a Z score.

1 | ```
Z.value(W, Wstar, n.in, n.out)
``` |

`W` |
Wilcoxon statistic for observed data. |

`Wstar` |
A vector of Wilcoxon statistics for a set of permuted data. |

`n.in` |
The number of items (SNPs) in the regions to be tested. |

`n.out` |
The number of items (SNPs) in the control regions. |

A list with two elements:

- Z.theoretical
which uses the theoretical mean of the Wilcoxon distribution under the null generated from n.in, n.out above

- Z.empirical
which uses Wstar to calculate an empirical estimate of the mean of the Wilcoxon distribution under the null

The function can also deal with combining W statistics from multiple strata, as is typical in a meta analysis of GWAS data, using van Elteren's method. Strata may be defined by different geography or different SNP chips.

Chris Wallace

1 2 3 4 5 6 7 8 |

wgsea documentation built on May 29, 2017, 7:02 p.m.

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