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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