cellHTS (version 1.42.0)

summarizeChannels: Normalization and transformation of dual-channel data

Description

Normalizes and/or transforms dual-channel data xraw of a cellHTS object by applying the function defined in fun.

Usage

summarizeChannels(x, fun = function(r1, r2, thresh) ifelse(r1>thresh, log2(r2/r1), as.numeric(NA)), adjustPlates, zscore, ...)

Arguments

x

a cellHTS object that has been configured.

fun

a user-defined function for the two channel summarization. fun takes two numeric vectors and returns a numeric vector of the same length. The default is to take the log2-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.

adjustPlates

scalar character string indicating the normalization method to apply to adjust for plate-to-plate variations (and possibly well-to-well variations). This is done before applying fun. Allowed values are "median", "mean", "shorth", "POC", "NPI", "negatives" and Bscore. If adjustPlates is missing (the default), no plate-wise correction will be performed.

zscore

indicates if the z-scores should be determined after normalization and transformation. If missing (default), the data will not be scored. Otherwise, it should be a character string, either "+" or "-", specifying the sign to use for the z-scores.

...

Further arguments that get passed on to the function implementing the normalization method chosen by adjustPlates. See the Details section and the normalizePlates function.

Value

An object of class cellHTS, which is a copy of the argument x, plus an additional slot xnorm containing the normalized data. This is an array of the same dimensions as xraw, except in the dimension corresponding to the number of channels, since the two-channel intensities have been combined into one intensity value.Moreover, the processing status of the cellHTS object is updated in the slot state to x$state["normalized"]=TRUE.Additional outputs may be given if adjustPlates="Bscore". Please refer to the help page of the Bscore function.

Details

For each plate and replicate of a two-color experiment, the function defined in fun is applied to relate the intensity values in the two channels of the cellHTS object. The default is to take the log2-ratio between the second and first channels, with a threshold on r1 (see the Usage section). This threshold should be ajusted by the user according to the data. For an example, see the Examples section.

If adjustPlates is not missing, the values for each channel will be corrected for plate effects before applying fun, by considering the chosen normalization method. The available options are adjustPlates="median" (median scaling), adjustPlates="mean" (mean scaling), adjustPlates="shorth" (scaling by the midpoint of the shorth), adjustPlates="POC" (percent of control), adjustPlates="negatives" (scaling by the average on the negative controls), adjustPlates="NPI" (normalized percent inhibition) and adjustPlates="Bscore" (B score method). For more details about these normalization options, please refer to normalizePlates. By default, adjustPlates is missing.

If zscore is not missing, a robust z-score is calculated based on the channel-summarized measurements. The z-score for each individual measurement will be determined for each plate and each well by subtracting the overall median and dividing by the overall mad. The allowed values for zscore ("+" or "-") are used to set the sign of the calculated z-scores. See summarizeReplicates for more details.

See Also

normalizePlates, Bscore, summarizeReplicates

Examples

 ## Not run: 
#     datadir <- system.file("DualChannelScreen", package = "cellHTS")
#     x <- readPlateData("Platelist.txt", "TwoColorData", path=datadir)
#     x <- configure(x, "Plateconf.txt", "Screenlog.txt", "Description.txt", path=datadir)
#     table(x$wellAnno)
# 
#     ## Define the controls for the different channels:
#     negControls=vector("character", length=dim(x$xraw)[4])
# 
#     ## 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$" 
#     posControls = vector("character", length=dim(x$xraw)[4])
#     ## channel 1 - no controls
#     ## channel 2 - geneC and geneD
#     posControls[2]="(?i)^geneC$|^geneD$"
# 
#     writeReport(x, posControls=posControls, negControls=negControls)
#     ## In this example, we first normalize each channel separately by plate median scaling. 
#     ## Then, we define a low intensity threshold for the measurements in the constitutive channel R1, 
#     ## which will be set to the 5
#     x = summarizeChannels(x, fun = function(r1, r2, 
#              thresh=quantile(r1, probs=0.05, na.rm=TRUE)) ifelse(r1>thresh, log2(r2/r1), as.numeric(NA)),
#       adjustPlates="median") 
#     ## Note that the plate median scaling is applied to each channel, prior to channel summarization.
#     ## Define the controls for the normalized intensities (only one channel):
#     negControls = vector("character", length=dim(x$xnorm)[4])
#     ## For the single channel, the negative controls are geneA and geneB 
#     negControls[1]= "(?i)^geneA$|^geneB$" 
#     posControls = vector("character", length=dim(x$xnorm)[4])
#     ## For the single channel, the negative controls are geneC and geneD 
#     posControls[1]="(?i)^geneC$|^geneD$"
#     writeReport(x, force=TRUE, plotPlateArgs=list(xrange=c(-3,3)), 
#          posControls=posControls, negControls=negControls)
#  ## End(Not run)