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

When analyzing two datasets that have different numbers of samples, this function can be used to assist the choice of a p value threshold for the tni.permutation() function, in order that RTN will return regulon results that have been generated with similar tradeoffs between Type I and Type II errors for both datasets. Doing this should help ensure that it is reasonable to compare the regulons in the two datasets.

1 | ```
tni.alpha.adjust(nB, nA, alphaA, betaA = 0.2)
``` |

`nB` |
a single integer specifying the number of samples in dataset 'B'. |

`nA` |
a single integer specifying the number of samples in dataset 'A'. |

`alphaA` |
a single numeric value specifying alpha for dataset 'A' (Type I error probability). |

`betaA` |
a single numeric value specifying beta for dataset 'A' (Type II error probability). |

Significance level for 'nB', given 'nA', 'alphaA' and 'betaA'.

The 'tni.alpha.adjust' function calls the `pwr.r.test`

function, which uses the 'uniroot' function to solve a power equation. The 'uniroot' function aims to find a root in a given interval, searching from lower to upper end-points. As the upper end-point must be strictly larger than the lower end-point, in order to avoid an error when searching the root, 'nA' must be greater than or equal to 'nB' (i.e. 'nB' is expected to be the smallest data set). Also, please note that 'uniroot' eventually will not find the root for the input arguments, especially when searching thresholds of low stringency (we suggest to avoid setting 'alphaA' > 0.01).

Mauro Castro, Gordon Robertson

1 2 | ```
# estimate 'alphaB' for 'nB', given 'nA', 'alphaA' and 'betaA'
alphaB <- tni.alpha.adjust(nB = 100, nA = 300, alphaA = 1e-5, betaA = 0.2)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.