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")