readQC {beadarray} | R Documentation |
Reads the standard format of Illumina quality control information and produces diagnostic plots
readQC(file, columns=list(Biotin="AVG.Signal.biotin", cy3_high="AVG.Signal.cy3_hyb_high", cy3_low="AVG.Signal.cy3_hyb_low", cy3_med="AVG.Signal.cy3_hyb_med", gene="AVG.Signal.gene", hs="AVG.Signal.high_stringency_hyb", house="AVG.Signal.housekeeping", labeling="AVG.Signal.labeling", mm="AVG.Signal.low_stringency_hyb_mm2", pm="AVG.Signal.low_stringency_hyb_pm", negative="AVG.Signal.negative"),skip=7,sep=",",header=T) plotQC(object,...)
file |
name of file containing qc information |
columns |
a vector of column names to read from the file |
skip |
number of lines of header information to ignore in the file |
header |
if TRUE the column names in the file are read |
sep |
a character string for the file separator |
object |
a ExpressionSetIllumina object containing QC information or QC object created by readQC |
... |
extra plotting arguments that can be sent to plotQC |
The default options are able to read a file which gives quality control information and put in a sensible data structure. The quality control files are generated by BeadStudio and given the file name _qc_info.csv by default.
The information read is given in a assayData structure with Signal (average expression), Var (standard error) and Detection matrices. The rows of each matrix are arrays in the experiment and columns are the average value of a particular control type.
A plot giving a overview of all the control types can be produced by using plotQC. We can also plot a particular control using singleQCPlot and specify whether to plot the average, standard deviation or detection.
readQC produces an assayData object with Signal, Var and Detection matrices
Mark Dunning
data(QC) QC$Signal data(BSData) QC = QCInfo(BSData)