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cellHTS2 (version 2.36.0)

imageScreen: Experiment-wide quality control plot of a cellHTS object

Description

Experiment-wide quality control plot of a scored cellHTS object.

Usage

imageScreen(object, ar=3/5, zrange=NULL, map=FALSE, anno=NULL, col=list(posNeg=rev(brewer.pal(11, "RdBu"))[c(1:5, rep(6, 3), 7:11)], pos=brewer.pal(9, "Greys")), nbImageBins=256, nbLegendBins=7)

Arguments

object
a cellHTS object that has already been scored (i.e. state(object)['scored']=TRUE).
ar
the desired aspect ration for the image plot (i.e. number of columns per number of rows)
zrange
the range of values to be mapped into the color scale. If missing, zrange will be set to the range of the score values stored in slot assayData of object.
map
a logical value that determines whether an image map should be created using tooltips to indicate the annotation at each position. It only makes sense to set it to TRUE when the function is called from writeReport function, so the default is FALSE.
anno
optional input giving the annotation information for the mapping. It should be a vector of the same size as the total number of featured in object. See details.
col
a list giving the colors for the plot. The first element posNeg is used if zrange[1]<0< code=""> and zrange[2]>0, the second if all values are either positive or negative.
nbImageBins
The number of color bins used in the map. Default is 256.
nbLegendBins
The number of color bins shown in the legend. Default is 7.

Details

This function creates an image plot that gives an overview of the whole set of score values stored in slot assayData of a scored cellHTS object. When the annotation mapping is performed, by default, anno is set to:
  1. (if object is annotated) The content of column named GeneSymbol or named GeneID (if the former is not available) of the featureData slot of object;
  2. The position within the plate, if object is not annotated.

References

Boutros, M., Bras, L.P. and Huber, W. (2006) Analysis of cell-based RNAi screens, Genome Biology 7, R66.

See Also

normalizePlates, summarizeChannels, scoreReplicates, summarizeReplicates, Data writeReport

Examples

Run this code
    data(KcViabSmall) 
    x <- KcViabSmall   
    x <- normalizePlates(x, scale="multiplicative", log=FALSE, method="median", varianceAdjust="none")
    x <- scoreReplicates(x, sign="-", method="zscore") 
    x <- summarizeReplicates(x, summary="min") 
    imageScreen(x, zrange=c(-5,5))

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