| summarizeReplicates {cellHTS2} | R Documentation |
This function summarizes the replicate values stored in slot assayData of a cellHTS object
and calculates a single score for each probe. Data are stored in slot assayData overridding its current content.
Currently this function is implemented only for single-color data.
summarizeReplicates(object, summary ="min")
object |
an object of class cellHTS that has already been normalized and scored (see details). |
summary |
a character string indicating how to summarize between replicate measurements. One of "min" (default), "mean", "median", "max", "rms", "closestToZero", or "FurthestFromZero" can be used (see details). |
A single value per probe is calculated by summarizing between scored replicates stored in the slot assayData of object. The summary is performed as follows:
summary="mean", the average of replicate values is considered;
summary="median", the median of replicate values is considered;
summary="max", the maximum of replicate intensities is taken;
summary="min", the minimum is considered, instead;
summary="rms", the square root of the mean squared value of the replicates (root mean square) is taken as a summary function;
summary="closestToZero", the value closest to zero is taken as a summary (useful when both sides of the distribution of z-score values are of interest);
summary="furthestFromZero", the value furthest from zero is taken as a summary (useful when both sides of the distribution of z-score values are of interest).
The cellHTS object with the summarized scored values stored in slot assayData. This is an object of class assayData corresponding to a single matrix of dimensions Features x 1.
Moreover, the processing status of the cellHTS object is updated
in the slot state to object@state[["scored"]]= TRUE.
W. Huber huber@ebi.ac.uk, Ligia Bras ligia@ebi.ac.uk
Boutros, M., Bras, L.P. and Huber, W. (2006) Analysis of cell-based RNAi screens, Genome Biology 7, R66.
normalizePlates,
summarizeChannels,
scoreReplicates,
imageScreen.
data(KcViabSmall)
# normalize
x <- normalizePlates(KcViabSmall, scale="multiplicative", method="median", varianceAdjust="none")
# score the replicates
x <- scoreReplicates(x, sign="-", method="zscore")
# summarize the replicates (conservative approach: take the minimum value between replicates)
x <- summarizeReplicates(x, summary="min")