estimateSmoothing {edgeR} | R Documentation |
This function is no longer recommended or required.
Use getPriorN
instead.
Estimate the prior weight, prior.n, using an approximate empirical Bayes rule given the estimate of the common dispersion. The prior weight determines how much smoothing takes place to squeeze tag/genewise estimates of the dispersion closer to the estimate of the common dispersion.
estimateSmoothing(object,verbose=TRUE)
object |
|
verbose |
logical, whether to write comments, default |
We are no longer recommending this function, as it produces variable results.
prior.n
is now set automatically using getPriorN
.
estimateSmoothing
produces an object of class DGEList
with the following components.
prior.n |
scalar; estimate of the prior weight, i.e. the smoothing parameter that indicates the weight to put on the common likelihood compared to the individual tag's likelihood; prior.n of 10 means that the common likelihood is given 10 times the weight of the individual tag/gene's likelihood in the estimation of the tag/genewise dispersion |
Mark Robinson, Davis McCarthy
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)) d<-estimateCommonDisp(d) prior.n<-estimateSmoothing(d)