twilight {twilight} | R Documentation

## Estimation of local false discovery rate

### Description

The function performs the successive exclusion procedure (SEP) as described in Scheid and Spang (2004).

### Usage

    twilight(xin, lambda = NULL, B = 0, boot.ci = 0.95, clus = NULL, verbose = TRUE)

### Arguments

`xin` | Numerical vector of u-values, p-values or a `twilight` object.
`lambda` | Numerical value denoting the penalty factor. If not specified, the function searchs for an appropriate regularization parameter.
`B` | Numerical value specifying the number of bootstrap samples. If not specified, no bootstrap estimates are calculated.
`boot.ci` | Numerical value denoting the probability value for bootstrap confidence intervals of local false discovery rate and prior pi0.
`clus` | A list or numerical value to be passed to `makeCluster(clus,...)` in `library(snow)`. If specified, bootstrapping is performed in parallel. No checks on `clus` are performed. Please make sure that `makeCluster(clus)` works properly in your environment.
`verbose` | Logical value for message printing.

### Details

See vignette.

### Value

Returns a `twilight` object consisting of a `data.frame` named `result` with variables

`pvalue` | Sorted input vector.
`qvalue` | q-values computed as described in Storey and Tibshirani (2003) with new estimate `pi0`.
`index` | Index of the original ordering.
`fdr` | Local false discovery rate averaged over 10 runs of SEP.
`mean.fdr` | Bootstrap estimate of local false discovery rate.
`lower.fdr` | Lower `boot.ci`-bootstrap confidence bound.
`upper.fdr` | Upper `boot.ci`-bootstrap confidence bound.

Values are sorted by `pvalue`.

### Note

Additional output consists of

`lambda` | Regularization parameter.
`pi0` | SEP estimate of prior probability.
`boot.pi0` | Bootstrap estimate and `boot.ci`-bootstrap confidence bounds.
`boot.ci` | Passes `boot.ci` for plotting.
`effect` | Histogram of effect size distributions averaged over 10 runs of SEP.

If `xin` is of class `twilight`, the remaining slots are filled with corresponding input values. If `xin` is not of class `twilight`, these slots remain free.

### Author(s)

Stefanie Scheid http://www.molgen.mpg.de/~scheid

### References

Scheid S and Spang R (2004): A stochastic downhill search algorithm for estimating the local false discovery rate, IEEE TCBB 1(3), 98–108.

Storey JD and Tibshirani R (2003): Statistical significance for genomewide studies, PNAS 100(16), 9440–9445.

### See Also

`twilight.pval`, `plot.twilight`

### Examples

    data(exfdr) # twilight object created by twilight with B=1000 bootstraps
    plot(exfdr,which="fdr")

[Package twilight version 1.1.0 Index]