Ringo (version 1.36.0)

upperBoundNull: function to estimate upper limit of null distribution

Description

The data is assumed to arise from a mixture of two distributions, a symmetric null distribution with its mode close to zero, and an alternative distribution that is stochastically larger than the null. This function tries to pinpoint the minimum of data values that are more likely to arise from the alternative distribution, i.e. an upper bound for values following the null distribution.

Usage

upperBoundNull(x, modeMethod = "shorth", limits = c(-1, 1), prob = 0.99, ...)

Arguments

x

numeric vector of data values

modeMethod

character string; which method to use for estimating the mode of the null distribution; see details

limits

numeric of length 2; data values within this range are used for estimating the mode of the null distribution

prob

quantile of the null distribution that will be used as an upper bound

...

additional arguments that are passed on to the function for mode estimation

Value

a single numeric value which is the estimated upper bound for the null distribution.

Details

For estimating the mode of the null distribution, current options are

"shorth"

the function shorth

"half.range.mode"

the function half.range.mode

"null"

does not estimate the mode from the data, but sets it to 0

See Also

shorth, half.range.mode

Examples

  exDir <- system.file("exData",package="Ringo")
  load(file.path(exDir,"exampleProbeAnno.rda"))
  load(file.path(exDir,"exampleX.rda"))
  smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
       modColumn = "Cy5", allChr = "9", winHalfSize = 400)
  apply(exprs(smoothX), 2, upperBoundNull)