cellHTS2 (version 2.36.0)

summarizeReplicates: Summarize between scored replicate values given in a cellHTS object to obtain a single value for each probe

Description

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.

Usage

summarizeReplicates(object, summary ="min")

Arguments

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).

Value

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.

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).

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, imageScreen.

Examples

    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")