getPriorN {edgeR} | R Documentation

## Get a Recommended Value for Prior N from DGEList Object

### Description

Returns the `lib.size` component of the `samples` component of DGEList object multiplied by the `norm.factors` component

### Usage

    getPriorN(y, design=NULL, prior.df=20)

### Arguments

`y` | a `DGEList` object with (at least) elements `counts` (table of unadjusted counts) and `samples` (data frame containing information about experimental group, library size and normalization factor for the library size)
`design` | numeric matrix (optional argument) giving the design matrix for the GLM that is to be fit. Must be of full column rank. If provided `design` is used to determine the number of parameters to be fit in the statistical model and therefore the residual degrees of freedom. If left as the default (`NULL`) then the `y$samples$group` element of the `DGEList` object is used to determine the residual degrees of freedom.
`prior.df` | numeric scalar giving the weight, in terms of prior degrees of freedom, to be given to the common parameter likelihood when estimating genewise dispersion estimates.

### Details

When estimating genewise dispersion values using `estimateTagwiseDisp` or `estimateGLMTagwiseDisp` we need to decide how much weight to give to the common parameter likelihood in order to smooth (or stabilize) the dispersion estimates. The best choice of value for the `prior.n` parameter varies between datasets depending on the number of samples in the dataset and the complexity of the model to be fit. The value of `prior.n` should be inversely proportional to the residual degrees of freedom. We have found that choosing a value for `prior.n` that is equivalent to giving the common parameter likelihood 20 degrees of freedom generally gives a good amount of smoothing for the genewise dispersion estimates. This function simply recommends an appropriate value for `prior.n`—to be used as an argument for `estimateTagwiseDisp` or `estimateGLMTagwiseDisp`—given the experimental design at hand and the chosen prior degrees of freedom.

### Value

`getPriorN` returns a numeric scalar

### Author(s)

Davis McCarthy, Gordon Smyth

### See Also

`DGEList` for more information about the `DGEList` class. `as.matrix.DGEList`.

### Examples

    # generate raw counts from NB, create list object
    y<-matrix(rnbinom(20,size=1,mu=10),nrow=5)
    d<-DGEList(counts=y,group=rep(1:2,each=2),lib.size=rep(c(1000:1001),2))
    getPriorN(d)

[Package edgeR version 3.36.0 Index]