StoreyBH {onlineFDR} | R Documentation

## StoreyBH: Offline FDR control using the St-BH procedure

### Description

Implements the Storey-BH algorithm for offline FDR control, as presented by Storey (2002).

### Usage

    StoreyBH(d, alpha = 0.05, lambda = 0.5)

### Arguments

`d` | Either a vector of p-values, or a dataframe with the column: p-value (‘pval’).
`alpha` | Overall significance level of the FDR procedure, the default is 0.05.
`lambda` | Threshold for Storey-BH, must be between 0 and 1. Defaults to 0.5.

### Details

The function takes as its input either a vector of p-values, or a dataframe with a column of p-values (‘pval’).

### Value

`ordered_d` | A dataframe with the original data `d` and the indicator function of discoveries `R`. Hypothesis i is rejected if the i-th p-value is less than or equal to (r/n)α, where r is the rank of the i-th p-value within an ordered set and n is the total number of hypotheses. If hypothesis i is rejected, `R[i] = 1` (otherwise `R[i] = 0`).

### References

Storey, J.D. (2002). A direct approach to false discovery rates. J. R. Statist. Soc. B: 64, Part 3, 479-498.

### Examples

    pvals <- c(2.90e-08, 0.06743, 0.01514, 0.08174, 0.00171,
            3.60e-05, 0.79149, 0.27201, 0.28295, 7.59e-08,
            0.69274, 0.30443, 0.00136, 0.72342, 0.54757)

    StoreyBH(pvals)

[Package onlineFDR version 2.2.0 Index]