Bon_EV {BonEV} | R Documentation |

## Bon_EV: A R Function of Improved Multiple Testing Procedure for Controlling False Discovery Rates

### Description

Bon_EV is an improved multiple testing procedure for controlling false discovery rates which is developed based on the Bonferroni procedure with integrated estimates from the Benjamini-Hochberg procedure and the Storey's q-value procedure. It controls false discovery rates through controlling the expected number of false discoveries.

### Usage

```
Bon_EV(pvalue, alpha)
```

### Arguments

`pvalue` |
The input data is a vector of P-values ranged from 0 to 1 |

`alpha` |
The alpha is the level of false discovery rates (FDR) to control for |

### Details

Bon_EV is a function for getting adjusted P-values with FDR controlled at level alpha.

### Value

Bon_EV produces a named list with the following components:

`raw_P_value` |
Vector of raw P-values |

`BH_adjp` |
Adjusted P-values from the Benjamini-Hochberg procedure |

`Storey_adjp` |
Adjusted P-values from the Storey's q-value procedure |

`Bon_EV_adjp` |
Adjusted P-values from the Bon-EV multiple testing procedure |

### Author(s)

Dongmei Li

### See Also

The qvalue package.

### Examples

```
library(qvalue)
data(hedenfalk)
summary(hedenfalk)
pvalues <- hedenfalk$p
adjp <- Bon_EV(pvalues, 0.05)
summary(adjp)
sum(adjp$Bon_EV_adjp <= 0.05)
```

*BonEV*version 1.0 Index]