Description Usage Arguments Value References

This function uses the perumtation results to calculate empirical p values for the variant-to-variant influences calculated by `error.prop`

. It can also optionally adjust these p values using Holm's step-down procedure, false discovery rate (fdr), or local false discovery rate (lfdr).

1 2 |

`data.obj` |
The object in which all results are stored. See |

`pairscan.obj` |
The object in which the results from the pairscan are stored. See |

`pval.correction` |
One of "holm", "fdr", "lfdr" or "none", indicating whether the p value correction method used should be the Holm step-down procedure, false discovery rate, local false discovery, or no correction rate respectively. |

`n.cores` |
An integer specifying the number of cores to be used in parallel processing. |

The data object is returned with a new list with two elements. The elements correspond to the two directions of influence: marker1 to marker2 and marker2 to marker1. Each element contains a table with the source and target variants, the empirical p values, and the adjusted p values, along with the effect size, standard error and t statistic for each interaction.

Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian journal of statistics, pages 65-70. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Societ. Series B (Methodological), 289-300. Liao, J.G., Lin, Y., Selvanayagam, Z.E., & Shih, W.J. (2004). A mixture model for estimating the local false discovery rate in DNA microarray analysis. Bioinformatics, 20(16), 2694-2701. doi:10.1093/bioinformatics/bth310

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