numFP {puma} | R Documentation

## Number of False Positives for a given proportion of True Positives.

### Description

Often when evaluating a differential expression method, we are interested in how well a classifier performs for very small numbers of false positives. This method gives one way of calculating this, by determining the number of false positives for a set proportion of true positives.

### Usage

    numFP(scores, truthValues, TPRate = 0.5)

### Arguments

`scores` | A vector of scores. This could be, e.g. one of the columns of the statistics of a `DEResult` object.
`truthValues` | A boolean vector indicating which scores are True Positives.
`TPRate` | A number between 0 and 1 identify the proportion of true positives for which we wish to determine the number of false positives.

### Value

An integer giving the number of false positives.

### Author(s)

Richard D. Pearson

### See Also

Related methods `plotROC` and `calcAUC`.

### Examples

    class1a <- rnorm(1000,0.2,0.1)
    class2a <- rnorm(1000,0.6,0.2)
    class1b <- rnorm(1000,0.3,0.1)
    class2b <- rnorm(1000,0.5,0.2)
    scores_a <- c(class1a, class2a)
    scores_b <- c(class1b, class2b)
    classElts <- c(rep(FALSE,1000), rep(TRUE,1000))
    print(numFP(scores_a, classElts))
    print(numFP(scores_b, classElts))

[Package puma version 1.8.1 Index]