RNAinteract (version 1.20.0)

computePValues: 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

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)

Value

An object of class RNAinteract.

Details

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

References

~put references to the literature/web site here ~

See Also

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")