NUSE: Normalized Unscaled Standard Errors (NUSE)

Description Arguments Details Author(s) See Also Examples

Description

Produce boxplot of Normalized Unscaled Standard Errors (NUSE) for the set of arrays. Alternatively, summary statistics or NUSE values can be extracted as data.frame.

Usage

NUSE(x, treename = "*", type = c("plot", "stats", "values"), qualopt = NULL, ...)

Arguments

x

object of class QualTreeSet.

treename

vector of tree names to export.

type

type of output, plot, stats or values.

qualopt

quality control option, i.e. ‘raw’, ‘adjusted’, ‘normalized’ or ‘all’.

...

optional arguments to be passed to nuseplot.

Details

Create boxplots of Normalized Unscaled Standard Errors (NUSE) for the set of arrays.

Alternatively it is possible to extract either the summary statistics as data.frame (type="stats") or all NUSE values as data.frame (type="values").

If an object of class QualTreeSet was created by fitting a probe level model with qualopt="all" then NUSE will plot or extract NUSE for "all" quality options. If you want to plot or extract NUSE for a certain quality option only, e.g. "normalized" data only, then you can use parameter qualopt with qualopt="<qualopt>".

Author(s)

Christian Stratowa

See Also

plotNUSE, nuseplot

Examples

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## Not run: 
## load existing ROOT scheme file and ROOT data file
scheme.test3 <- root.scheme(paste(path.package("xps"),"schemes/SchemeTest3.root",sep="/"))
data.test3 <- root.data(scheme.test3, paste(path.package("xps"),"rootdata/DataTest3_cel.root",sep="/"))

## qualification - rlm
rlm.all <- rmaPLM(data.test3, "tmp_Test3RLMall", filedir=getwd(), tmpdir="", qualopt="all", option="transcript", add.data=FALSE)

## plot expression levels
if (interactive()) {
NUSE(rlm.all)
NUSE(rlm.all, qualopt="normalized")
qcNUSE <- NUSE(rlm.all, type="stats")
qcNUSE <- NUSE(rlm.all, type="values")
qcNUSE <- NUSE(rlm.all, treename="TestA1_normalized.rlm", type="stats")
qcNUSE <- NUSE(rlm.all, treename="TestA1_normalized.rlm", type="values")
}

## End(Not run)

xps documentation built on May 2, 2018, 2:33 a.m.