DESeq2 (version 1.8.2)

estimateBetaPriorVar: 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. For advanced users to use this function, first run estimateMLEForBetaPriorVar and then run estimateBetaPriorVar.

Usage

estimateBetaPriorVar(object, betaPriorMethod = c("weighted", "quantile"), upperQuantile = 0.05)
estimateMLEForBetaPriorVar(object, maxit = 100, useOptim = TRUE, useQR = TRUE)

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

maxit

as defined in link{nbinomWaldTest}

useOptim

as defined in link{nbinomWaldTest}

useQR

as defined in link{nbinomWaldTest}

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