summarizeReplicates: Summarize between scored replicate values given in a cellHTS...

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


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.

This function is implemented for single- and multi-channel data.


summarizeReplicates(object, summary ="min")



an object of class cellHTS that has already been normalized and scored (see details).


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:

  • If summary="mean", the average of replicate values is considered;

  • If summary="median", the median of replicate values is considered;

  • If summary="max", the maximum of replicate intensities is taken;

  • If summary="min", the minimum is considered, instead;

  • If summary="rms", the square root of the mean squared value of the replicates (root mean square) is taken as a summary function;

  • If 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);

  • If 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 matrices of dimensions Features x 1 for each channel. Moreover, the processing status of the cellHTS object is updated in the slot state to object@state[["scored"]]= TRUE.


W. Huber, Ligia Bras


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

See Also

normalizePlates, summarizeChannels, scoreReplicates, imageScreen.


    # 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")

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