ROC {cellHTS2} | R Documentation

## Creates an object of class "ROC" which can be plotted as a ROC curve

### Description

The function `ROC` construct an object of S4 class `ROC`, which represents a receiver-operator-characteristic curve, from the data of the annotated positive and negative controls in a scored `cellHTS` object.

### Usage

    ## S4 method for signature 'cellHTS':
    ROC(object, positives, negatives)
    ## S4 method for signature 'ROC, missing':
    plot(x, col="darkblue", type="l", main = "ROC curve", ...)
    ## S4 method for signature 'ROC':
    lines(x, ...)

### Arguments

`object` | a `cellHTS` object which replicate data have already been scored and summarized (see details).
`positives` | a list or vector of regular expressions specifying the name of the positive control(s). See the details for the argument `posControls` of `writeReport` function. The default is `"^pos$"`.
`negatives` | a vector of regular expressions specifying the name of the negative control(s). See the details for the argument `negControls` of `writeReport` function. The default is `"^neg$"`.
`x` | a `ROC` object obtained using function `ROC`.
`col` | the graphical parameter for color; see `par` for details.
`type` | the graphical parameter giving the type of plot desired; see `par` for details.
`main` | the graphical parameter giving the desired title of plot; see `par` for details.
`...` | other graphical parameters as in `par` may be also passed as arguments.

### Details

The `cellHTS` object `object` must be already scored (`state(object)["scored"]=TRUE`), and selection proceeds from large to small values of this single per-probe score. Furthermore, `object` is expected to contain positive and negative controls annotated in the column `controlStatus` of the `featureData` slot - which can be accessed via `wellAnno(object)`. The arguments `positives` and `negatives` should be given as regular expression patterns specifying the name of the positive(s) and negative(s) controls, respectivey. By default, if `positives` is not given, pos will be taken as the name for the wells containing positive controls. Similarly, if `negatives` is missing, by default neg will be considered as the name used to annotate the negative controls. The content of `posControls` and `negControls` are passed to `regexpr` for pattern matching within the well annotation (see examples for `summarizeChannels`). If the assay is a two-way experiment, `positives` should be a list with components `act` and `inh`, specifying the name of the activators, and inhibitors, respectively. In this case, the ROC curve is constructed based on the absolute values of `Data(object)`.

### Value

An S4 object of class `ROC`. There are methods `show`, `plot` and `lines`.

### Author(s)

Ligia P. Bras ligia@ebi.ac.uk

### Examples

        data(KcViabSmall)
        x <- normalizePlates(KcViabSmall, scale="multiplicative", log=FALSE, method="median", varianceAdjust="byExperiment")
        x <- scoreReplicates(x, sign="-", method="zscore")
        x <- summarizeReplicates(x, summary="mean")
        y <- ROC(x)
        plot(y)
        lines(y, col="green")
        show(y)

[Package cellHTS2 version 2.4.1 Index]