runQC: Run quality control
In piano: Platform for integrative analysis of omics data

Description Usage Arguments Details Value Author(s) References See Also Examples

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 `ArrayData`.
`rnaDeg`	should RNA degradation be detected? Defaults to `TRUE`.
`nuseRle`	should Normalized Unscaled Standard Errors (NUSE) and Relative Log Expressions (RLE) be calculated? Defaults to `TRUE`.
`hist`	produce histograms of expression values? Defaults to `TRUE`.
`boxplot`	produce boxplots of expression values? Defaults to `TRUE`.
`pca`	should PCA be run? Defaults to `TRUE`.
`colorFactor`	a number specifying which column of the setup (given by the `ArrayData` object) should be used for coloring information for the PCA. Defaults to 1.
`colors`	a character vector of colors to be used in the PCA plot.
`save`	should the figures be saved? Defaults to `FALSE`.
`verbose`	verbose? Defaults to `TRUE`.

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:

1 2	# 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)