emCDF {beadarrayFilter}R Documentation

Function to plot the empirical cumulative density functions (ecdf)

Description

Plots the ecdf for different thresholding strategies as discussed in Forcheh et al. (2012).

Usage

emCDF(iccResults, iccQuant = 1)

Arguments

iccResults

A list containing a number of components obtained from applying the iccFun function. It contaning the ICCs to be used for plotting.

iccQuant

Refers to the number summary described in Forcheh et al. (2012). It can be a vector of quantiles or a single value. For example, iccQuant = c(0,0.25,0.5,0.75,1) means that the ecdf be plotted for the minimum ICC, 0.25, 0.5, 0.75 for the 25, 50, and 75 quantiles and the maximum ICC respectively, while iccQuant = 1 means that the ecdf be plotted only for one number summary of interest.

Author(s)

Anyiawung Chiara Forcheh, Geert Verbeke, Adetayo Kasim, Dan Lin, Ziv Shkedy, Willem Talloen, Hinrich WH Gohlmann, Lieven Clement.

References

Neuwirth, E. RColorBrewer: ColorBrewer palettes. R package version 1.0-2., 2007.

Examples

require(beadarrayExampleData)
data(exampleSummaryData)
exampleSummaryDatalog2 <- channel(exampleSummaryData, "G")
exampleSummaryDataNorm <- normaliseIllumina(exampleSummaryDatalog2, 
method = "quantile", transform = "none")
aaa<-na.omit(data.frame(I(rownames(exprs(exampleSummaryDataNorm))),exprs(exampleSummaryDataNorm)))
ProbeID <- aaa[,1][1:100]
    eSet <- na.omit(exprs(exampleSummaryDataNorm))[1:100,]
    stddev <- na.omit(se.exprs(exampleSummaryDataNorm))[1:100,]
    nSet <- na.omit(attributes(exampleSummaryDataNorm)$assayData$nObservations)[1:100,]
    seSet<-stddev/sqrt(nSet)
    iccResults<-iccFun(eSet,seSet,nSet,ProbeID =ProbeID ,iccQuant=c(0,0.25,0.5,1),
    diffIcc=TRUE,keepData=TRUE)
    emCDF(iccResults, iccQuant= c(0,0.25,0.5,1))

[Package beadarrayFilter version 1.1.0 Index]