\name{computePValues} \alias{computePValues} \title{ compute p-values } \description{ Compute p-values for genetic interactions terms. Assess if genetic interaction term is different from zero. } \usage{ computePValues(sgi, method = "pooled.ttest", mixTemplateQuery = TRUE, p.adjust.function = function(x) { p.adjust(x, method = "BH")}, verbose = 0) } \arguments{ \item{sgi}{ An object of class \code{\link{RNAinteract}}. } \item{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 \link{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. } \item{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 \code{mixTemplateQuery = TRUE}. Else a p-value is computed independently for both cases. } \item{p.adjust.function}{ A function that corrects the p-values for multiple testing. Default method is the Benjamini-Hochberg method. } \item{verbose}{Either 0 (default, no output), 1 (minimum output), or 2 (outout)} } \details{ Computes p-values from a t-test, using the bioconductor package limma, or with a multidimensional Hotelling T^2 test. } \value{ An object of class \code{\link{RNAinteract}}. } \references{ ~put references to the literature/web site here ~ } \author{ Bernd Fischer } \seealso{ \code{\link{RNAinteract-package}} } \examples{ 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") } \keyword{ manip } \keyword{ htest } \keyword{ multivariate }