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

View source: R/summarizeReplicates.R

Apply a sigmoidal transformation with parameters z0 and lambda to the summarized scored values stored in a `cellHTS`

object.
The obtained results are called *calls* and are stored in slot `assayData`

, overridding its current content.

Currently this function is implemented only for single-color data.

1 | ```
scores2calls(x, z0, lambda)
``` |

`x` |
an object of class |

`z0` |
a numeric value giving the centre of the sigmoidal transformation. See details. |

`lambda` |
a numeric value (>0) that corresponds to the parameter |

This function applies a sigmoidal transformation with parameters z0 and lambda to the single per-probe score values stored
in a `cellHTS`

object. The obtained results are called *calls*. The transformation is given by:

*1 / (1 + exp(-lambda * (z- z0)))*

where `z`

are the score values, `z0`

is the centre of the sigmoidal transformation, and the `lambda`

is a parameter that controls the smoothness of the transformation. The higher is `lambda`

, more steeper is the transition from lower to higher values. `lambda`

should be `> 0`

, but usually it makes more sense to use a value `>=1`

.

This transformation maps the score values to the interval `[0,1]`

, and is intended to expand the scale of scores with intermediate values and shrink the ones showing extreme values, therefore making the difference between intermediate phenotypes larger.

The `cellHTS`

object with the call values stored in slot `assayData`

. This is an object of class `assayData`

corresponding to a single matrix of dimensions `Features x 1`

.

W. Huber huber@ebi.ac.uk, Ligia Braz 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`

,
`summarizeReplicates`

,
`imageScreen`

.

1 2 3 4 5 6 7 8 9 10 11 | ```
data(KcViabSmall)
x <- normalizePlates(KcViabSmall, scale="multiplicative", method="median", varianceAdjust="none")
x <- scoreReplicates(x, sign="-", method="zscore")
x <- summarizeReplicates(x, summary="min")
xc <- scores2calls(x, z0=1.5, lambda=2)
plot(Data(x), Data(xc), col="blue", xlab="z-scores", ylab="calls", main=expression(1/(1+e^{-lambda *(z-z[0])})))
if(require(splots)) {
sp = split(Data(xc), plate(xc))
plotScreen(sp, zrange=c(0,1), fill=c("white", "red"), na.fill="yellow",
main="Calls", ncol=3L)
}
``` |

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