Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/summarizeReplicates.R
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.
1 | summarizeReplicates(object, summary ="min")
|
object |
an object of class |
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:
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 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
.
1 2 3 4 5 6 7 | 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")
|
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