summarizeChannels: Summarization of dual-channel data
In cellHTS2: Analysis of cell-based screens - revised version of cellHTS

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

Combines plate intensities (raw or already corrected in a per-plate fashion) from multi-channel data stored in slot assayData of a cellHTS instance by applying the function defined in fun.

1 2	summarizeChannels(object, fun = function(r1, r2, thresh=-Inf) ifelse(r1>thresh, r2/r1, as.numeric(NA)))

`object`	an object of class `cellHTS` that has been configured. See details.
`fun`	a user-defined function for the multi channel summarization. `fun` takes as many numeric vectors as there are channels, names `r1, r2, etc.`, and returns a single numeric vector of the same length. The default is to take the ratio between the second and first channels, with a threshold on `r1` shown above in the Usage section that should be set by the user.

For each plate and replicate of a multi-color experiment, the function defined in fun is applied to relate the intensity values in the respective channels of the cellHTS object. The default is to take the ratio between the second and first channels, with a threshold on r1 (see the Usage section). This threshold should be adjusted by the user according to the data. For an example, see the Examples section. This function uses the content of slot assayData of object and can be applied either to raw data or after per-plate correction of the intensity values in each channel using function normalizePlates. This choice depends on channel summarization method that one intends to apply (i.e., the function given by argument fun).

An object of class cellHTS with the summarized multi-channel intensities stored in slot assayData. This is an object of class assayData containing one matrix with the summarized channel data (dimensions nrFeatures x nrSamples).

Ligia Bras ligia@ebi.ac.uk, Wolfgang Huber huber@ebi.ac.uk

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

normalizePlates, scoreReplicates, summarizeReplicates.

    data(dualCh)
    x <- dualCh
    table(wellAnno(x))

    ## Define the controls for the different channels:
    negControls=vector("character", length=dim(Data(x))[3])

    ## channel 1 - gene A
    ## case-insensitive and match the empty string at the beginning and end of a line (to distinguish between "geneA" and "geneAB", for example, although this is not a problem for the well annotation in this example)

    negControls[1]= "(?i)^geneA$"  
    ## channel 2 - gene A and geneB
    negControls[2]= "(?i)^geneA$|^geneB$" 
    posControls = vector("character", length=dim(Data(x))[3])
    ## channel 1 - no controls
    ## channel 2 - geneC and geneD
    posControls[2]="(?i)^geneC$|^geneD$"
 ## Not run: 
    writeReport(cellHTSlist=list("raw"=x), map=TRUE, plotPlateArgs=TRUE, posControls=posControls, negControls=negControls)
 
## End(Not run)
    ## In this example, we first normalize each channel separately by 
    ## plate median scaling (no variance adjustment), since we need to make the measurements 
    ## comparable across plates for the next step of channel summarization:
        xn = normalizePlates(x, scale="multiplicative", log=FALSE, method="median", varianceAdjust="none") 
    ## Then, we define a low intensity threshold for the measurements in the constitutive channel R1, 
    ## which will be set to the 5% quantile of the overall plate median corrected intensities in R1, 
    ## and take the ratio R2/R1.
        xn = summarizeChannels(xn, fun = function(r1, r2, 
             thresh=quantile(r1, probs=0.05, na.rm=TRUE)) ifelse(r1>thresh, r2/r1, as.numeric(NA))) 
    ## After channel summarization, we take the log2 and apply plate median normalization, 
    ## and opt to not adjust the variance:
    xn = normalizePlates(xn, scale="multiplicative", log=TRUE, method="median", varianceAdjust="none") 
    ## Define the controls for the normalized and summarized intensities (only one channel):
    negControls = vector("character", length=dim(Data(xn))[3])
    ## For the single channel, the negative controls are geneA and geneB 
    negControls[1]= "(?i)^geneA$|^geneB$" 
    posControls = vector("character", length=dim(Data(xn))[3])
    ## For the single channel, the negative controls are geneC and geneD 
    posControls[1]="(?i)^geneC$|^geneD$"
 ## Not run: 
    writeReport(cellHTSlist=list("raw"=x, "normalized"=xn), force=TRUE, map=TRUE, plotPlateArgs=list(xrange=c(-3,3)), 
         posControls=posControls, negControls=negControls)
 
## End(Not run)

    ## Another option could be to just take the log2 of the ratio between R2 and R1 raw intensities:
    xn1 = summarizeChannels(x, fun = function(r1, r2) log2(r2/r1))