empiricalEnrichmentMeanCDF {transite}R Documentation

Significance of Observed Mean

Description

empiricalEnrichmentMeanCDF returns an estimate of the significance of the observed mean, given a vector of means based on random permutations of the data.

Usage

empiricalEnrichmentMeanCDF(random.means, actual.mean,
  alternative = c("two.sided", "less", "greater"), conf.level = 0.95)

Arguments

random.means

numeric vector of means based on random permutations of the data (empirical null distribution)

actual.mean

observed mean

alternative

side of the test, one of the following: "two.sided", "less", "greater"

conf.level

confidence level for the returned confidence interval.

Value

A list with the following components:

p.value.estimate the estimated p-value of the observed mean
conf.int the confidence interval around that estimate

See Also

Other k-mer functions: calculateKmerEnrichment, checkKmers, computeKmerEnrichment, drawVolcanoPlot, generateKmers, generatePermutedEnrichments, homopolymerCorrection, permTestGeometricMean, runKmerSPMA, runKmerTSMA

Examples

test.sd <- 1.0
test.null.distribution <- rnorm(n = 10000, mean = 1.0, sd = test.sd)

empiricalEnrichmentMeanCDF(test.null.distribution, test.sd * 2, "greater")

[Package transite version 1.2.1 Index]