decideTests {limma}R Documentation

Compute Matrix of Hypothesis Test Results

Description

Classify a series of related t-statistics as up, down or not significant.

Usage

decideTests(object,method="separate",adjust.method="fdr",p.value=0.05)

Arguments

object MArrayLM object output from eBayes from which the t-statistics may be extracted.
method character string specify how probes and contrasts are to be combined in the multiple testing strategy. Choices are "separate", "global", "heirarchical", "nestedF" or any partial string.
adjust.method character string specifying p-value adjustment method. See p.adjust for possible values.
p.value numeric value between 0 and 1 giving the desired size of the test

Details

These functions implement multiple testing procedures for determining whether each statistic in a matrix of t-statistics should be considered significantly different from zero. Rows of tstat correspond to genes and columns to coefficients or contrasts.

The setting method="separate" is equivalent to using topTable separately for each coefficient in the linear model fit, and will give the same lists of probes if adjust.method is the same. Note that the defaults for adjust.method are different for decideTests and topTable. method="global" will treat the entire matrix of t-statistics as a single vector of unrelated tests. method="heirarchical" adjusts down genes and then across contrasts. method="nestedF" adjusts down genes and then uses classifyTestsF to classify contrasts as significant or not for the selected genes.

Value

An object of class TestResults. This is essentially a numeric matrix with elements -1, 0 or 1 depending on whether each t-statistic is classified as significantly negative, not significant or significantly positive respectively.

Author(s)

Gordon Smyth

See Also

An overview of linear model functions in limma is given by 5.LinearModels.


[Package limma version 1.9.6 Index]