pifdr {GGtools} | R Documentation

## utility for computing plug-in FDR

### Description

utility for computing plug-in FDR

### Usage

    pifdr( obs, perms, legacy=FALSE, trimToUnit = TRUE, ... )

### Arguments

`obs` | observed association scores
`perms` | vector of association scores under permutation; length should be integer multiple of `length(obs)`
`legacy` | logical, if TRUE, use the approximate version of pifdr() available before 12/30/2013, with additional arguments if desired
`trimToUnit` | logical, if TRUE, values greater than 1 are replaced by 1. Such values can occur, for example, with relatively small sample sizes.
`...` | extra arguments passed if legacy is TRUE

### Details

Revised 12/30/13 to employ hist() to rapidly bin the permuted values.

Use `legacy=TRUE` to obtain the approximate implementation, for which the following remarks held: “As currently implemented the algorithm is quadratic in `length(obs)`. While it is possible to get a unique FDR value for every element of `obs`, an approximate approach yields practically identical precision and by default this will be used for `obs` with length 2000 or more. In this case, `approx` is used with `rule=2` to interpolate from the grid-based FDR estimates back to the data values.” Additional parameters `npts` and `applier` may be supplied if `legacy` is set to TRUE.

`npts` defined the number of points spanning the range of `obs` to be used for a lossy grid-based computation only used if `length(obs)>npts`.

`applier` is to be an `sapply`-like function.

### Value

vector of plug-in FDR estimates congruent to `obs`

### References

Hastie Tibshirani and Friedman Elements of Statistical Learning ch 18.7

### Examples

    set.seed(1234)
    op = par(no.readonly=TRUE)
    par(mfrow=c(2,2))
    X = c(rchisq(30000,1),rchisq(300,10))
    Y = rchisq(30300*3,1)
    qqplot(Y, X, xlab="null", ylab="observed")
    hist(pp <- pifdr(X,Y), xlab="plug-in FDR", main=" ")
    library(multtest)
    rawp = 1-pchisq(X, 1)
    MT <- mt.rawp2adjp(rawp)
    MT2 = MT[[1]][order(MT[[2]]),]
    plot(MT2[,"BH"], pp, xlab="BH FDR", ylab="plug-in FDR")
    par(op)

[Package GGtools version 5.18.0 Index]