estimateBetaPriorVar {DESeq2} | R Documentation

## Steps for estimating the beta prior variance

### Description

These lower-level functions are called within `DESeq` or `nbinomWaldTest`. End users should use those higher-level function instead. NOTE: `estimateBetaPriorVar` returns a numeric vector, not a DESEqDataSet! For advanced users: to use these functions, first run `estimateMLEForBetaPriorVar` and then run `estimateBetaPriorVar`.

### Usage

    estimateBetaPriorVar(
      object,
      betaPriorMethod = c("weighted", "quantile"),
      upperQuantile = 0.05,
      modelMatrix = NULL
    )

    estimateMLEForBetaPriorVar(
      object,
      maxit = 100,
      useOptim = TRUE,
      useQR = TRUE,
      modelMatrixType = NULL
    )

### Arguments

`object` | a DESeqDataSet
`betaPriorMethod` | the method for calculating the beta prior variance, either "quanitle" or "weighted": "quantile" matches a normal distribution using the upper quantile of the finite MLE betas. "weighted" matches a normal distribution using the upper quantile, but weighting by the variance of the MLE betas.
`upperQuantile` | the upper quantile to be used for the "quantile" or "weighted" method of beta prior variance estimation
`modelMatrix` | an optional matrix, typically this is set to NULL and created within the function
`maxit` | as defined in `link{nbinomWaldTest}`
`useOptim` | as defined in `link{nbinomWaldTest}`
`useQR` | as defined in `link{nbinomWaldTest}`
`modelMatrixType` | an optional override for the type which is set internally

### Value

for `estimateMLEForBetaPriorVar`, a DESeqDataSet, with the necessary information stored in order to calculate the prior variance. for `estimateBetaPriorVar`, the vector of variances for the prior on the betas in the `DESeq` GLM

[Package DESeq2 version 1.32.0 Index]