ROC.FCS {rflowcyt} | R Documentation

## ROC (Receiver Operating Characteristic) Curve: Percentage Positives for Flow Cytometry data

### Description

This function plots an ROC curve based on cutoff values from the observed combined dataset of hivpos and hivneg, which both are vectors of patient-specific percentage positives based on the 99.9th percentile of the corresponding control sample distribution. The output contains the sensitivities, 1-specificity,and the observed dataset, cutoff values.

### Usage

    ROC.FCS(hivpos, hivneg, lineopt = 1, colopt = 1, overlay = FALSE)

### Arguments

`hivpos` | numerical vector of percentage positives for the HIV positive individuals/samples for a given condition
`hivneg` | numerical vector of the percentage positives for the HIV negative individuals/samples for a given condition
`lineopt` | numerical value for the lty option of the plot (line type)
`colopt` | numerical value for the col option of the plot (color type)
`overlay` | Boolean expression as to whether or not the plot is an overlay

### Details

See 'PerPosROC' in the 'rfcdorig' package for a description of the input data and how percentage positives are defined.

The ROC curve in the example demonstrates that there is higher predictive ability of using the GAG stimulated samples rather than the PolA or PolB stimulated samples.

### Value

Let T be the the percentage positives, c be a given value in c.obs, and HIV+ defined as among HIV positive individuals, and HIV- defined as among HIV negative individuals.

`sensitivity` | numerical vector of the sensitivity=P(T>c | HIV+) calculated corresponding to a given cut-off in c.obs
`spec.complement` | numerical vector of 1-specificity= P(T>c | HIV -)corresponding to a given cut-off in c.obs
`c.obs` | a numerical vector of the cutoffs which were taken to be the values of the observations (the values of the percentage positives of both the HIV positive and HIV negative data)

### Author(s)

A.J. Rossini and J.Y. Wan

### References

Zoe Moodie and Mario Roederer

### See Also

`PercentPos.FCS`, data 'PerPosROC' in 'rfcdorig' package, `percentile.FCS`

### Examples

    if (require(rfcdmin)){

    data(PerPosROCmin)

    #plotting the gag stimulated 100* percent positives
    if (interactive()==TRUE){
    GAG<-ROC.FCS(hivpos.gag, hivneg.gag)
    #plotting the pola stimulated 100* percent positives
    POLA<-ROC.FCS(hivpos.pola, hivneg.pola, lineopt=2, colopt=2, overlay=TRUE)
    #plotting the polb stimulated 100* percent positives
    POLB<-ROC.FCS(hivpos.polb, hivneg.polb, lineopt=4, colopt=3, overlay=TRUE)
    legend(0.7, 0.7, c("gag", "polA", "polB"), col = c(1,2,3), lty=c(1,2,4))
    }

    }

[Package rflowcyt version 1.2.0 Index]