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

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)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(cellHTS2)
Loading required package: RColorBrewer
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: genefilter
Loading required package: splots
Loading required package: vsn
Loading required package: hwriter
Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: grid
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/cellHTS2/ROC.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ROC
> ### Title: Creates an object of class "ROC" which can be plotted as a ROC
> ###   curve
> ### Aliases: ROC ROC,cellHTS-method plot,ROC,missing-method
> ###   lines,ROC-method
> ### Keywords: univar
> 
> ### ** 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)
ROC object derived from the 'one-way assay' cellHTS object called 'KcViabSmall'.
Positive control: 'pos'. 
Negative control: 'neg'
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>