computePValues: compute p-values
In RNAinteract: Estimate Pairwise Interactions from multidimensional features

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.

computePValues(sgi,
               method = "pooled.ttest",
               mixTemplateQuery = TRUE,
               p.adjust.function = function(x) { p.adjust(x, method = "BH")},
               verbose = 0)

`sgi`	An object of class `RNAinteract`.
`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 `mixTemplateQuery = TRUE`. Else a p-value is computed independently for both cases.
`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 ~

RNAinteract-package

data("sgi")
sgi <- computePValues(sgi, method = "HotellingT2")
# Hotelling T^2 test will provide one p-value for all channels, PV will be the same
# for all channels in this case
PV <- getData(sgi, type="p.value", format="targetMatrix", channel="nrCells")