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

Compute p-values for genetic interactions terms. Assess if genetic interaction term is different from zero.

1 2 3 4 5 | ```
computePValues(sgi,
method = "pooled.ttest",
mixTemplateQuery = TRUE,
p.adjust.function = function(x) { p.adjust(x, method = "BH")},
verbose = 0)
``` |

`sgi` |
An object of class |

`method` |
The method used to compute p-values. One of "pooled.ttest","ttest", "limma", "HotellingT2". For "ttest" a Student t-test is applied for each gene pair. The variance is estimated locally for each gene pair. For "pooled.ttest", a pooled variance is estimated from all gene pairs. The variance applied for each gene pair is the maximum of the pooled and the local variance estimate. This method obtains conservative p-values. For "limma" mediates between the local and the global variance estimation in a Bayesian framework. The limma-package is applied to compute the p-values. For "HotellingT2" Hotelling-T^2 statistics is computed jointly for all dimensions. It results in a single p-value summarizing all channels. For simplification the p-values are stored in a matrix of dimension genes x genes x screens x channels and the p-values are repeated for each channel. The same holds for q-values. |

`mixTemplateQuery` |
If a gene-pair is measured twice as template-query and as query-template, a single p-value is computed by combining all measurements, if |

`p.adjust.function` |
A function that corrects the p-values for multiple testing. Default method is the Benjamini-Hochberg method. |

`verbose` |
Either 0 (default, no output), 1 (minimum output), or 2 (outout) |

Computes p-values from a t-test, using the bioconductor package limma, or with a multidimensional Hotelling T^2 test.

An object of class `RNAinteract`

.

Bernd Fischer

~put references to the literature/web site here ~

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