runQC | R Documentation |
Performs a set of quality control methods and produces the results as figures.
runQC( arrayData, rnaDeg = TRUE, nuseRle = TRUE, hist = TRUE, boxplot = TRUE, pca = TRUE, colorFactor = 1, colors = c("red", "green", "blue", "yellow", "orange", "purple", "tan", "cyan", "gray60", "black", "white"), save = FALSE, verbose = TRUE )
arrayData |
an object of class |
rnaDeg |
should RNA degradation be detected? Defaults to |
nuseRle |
should Normalized Unscaled Standard Errors (NUSE) and
Relative Log Expressions (RLE) be calculated? Defaults to |
hist |
produce histograms of expression values? Defaults to
|
boxplot |
produce boxplots of expression values? Defaults to
|
pca |
should PCA be run? Defaults to |
colorFactor |
a number specifying which column of the setup (given by
the |
colors |
a character vector of colors to be used in the PCA plot. |
save |
should the figures be saved? Defaults to |
verbose |
verbose? Defaults to |
This function is essentially a wrapper for various available quality control
functions for AffyBatch
objects and normalized microarray data. RNA
degradation (rnaDeg=TRUE
) and NUSE & RLE (nuseRle=TRUE
)
require raw data (a dataRaw
element in the ArrayData
object).
The PCA uses prcomp
on centralized normalized data.
Typical usages are:
# Run all quality controls: runQC(arrayData)
Does not return any object.
Leif Varemo piano.rpkg@gmail.com and Intawat Nookaew piano.rpkg@gmail.com
Brettschneider J, Collin F, Bolstad BM, and Speed TP. Quality assessment for short oligonucleotide arrays. Technometrics. (2007) In press
piano, loadMAdata
,
diffExp
, AffyRNAdeg
,
fitPLM
,
AffyBatch
, prcomp
# Get path to example data and setup files: dataPath <- system.file("extdata", package="piano") # Load normalized data: myArrayData <- loadMAdata(datadir=dataPath, dataNorm="norm_data.txt.gz", platform="yeast2") # Run PCA only: runQC(myArrayData,rnaDeg=FALSE, nuseRle=FALSE, hist=FALSE, boxplot=FALSE)
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