EstimateDEBDisp {DoubleExpSeq} | R Documentation |

## DEB-Seq: Empirical Bayes Estimates of Dispersion for a Double Binomial Distribution

### Description

Calculation of shrunken dispersion estimates via a 2-parameter empirical bayes method.

### Usage

```
EstimateDEBDisp(y,m,groups=NULL,neff=NULL,S=NULL,optim.method=c("BFGS","Nelder-Mead"))
```

### Arguments

`y` |
numeric matrix of inclusion counts. |

`m` |
numeric matrix of total counts: inclusion + exclusion. |

`groups` |
vector or factor giving the experimental group/condition for each sample/library. Default NULL. |

`neff` |
numeric vector of length equal to the number of rows of "y" where each value is the effective sample size for the event. Default is NULL in which case the effective sample size is calculated within the function. |

`S` |
numeric vector of length equal to the number of rows of "y" where each value is the random variable for each event whose distribution across exons is gamma. Default is NULL in which case the vector is calculated internally. |

`optim.method` |
character string determining which optimization routine to use for estimating the parameters of the prior distribution. Default is "BFGS". |

### Details

The shrunken dispersion estimates are a function of 2 parameters of the generalized beta prime distribution which are estimated via maximum likelihood resulting in empricaly bayes shinkage of the dispersion parameter.

### Value

vector of length equal to the number of rows of "y" where each value is the estimate of dispersion.

### Author(s)

Sean Ruddy

### Examples

```
data(exon)
dispersions <- EstimateDEBDisp( counts, offsets, groups)
```

*DoubleExpSeq*version 1.1 Index]