estimateTagwiseDisp {edgeR} | R Documentation |
Estimates tagwise dispersion values by an empirical Bayes method based on weighted conditional maximum likelihood.
estimateTagwiseDisp(object, prior.n=getPriorN(object), trend="movingave", prop.used=0.3, method="grid", grid.length=200, tol=1e-06, verbose=FALSE)
object |
object of class |
prior.n |
numeric scalar, smoothing parameter that indicates the weight to give to the common likelihood compared to the individual tag's likelihood; default |
trend |
method for allowing the prior distribution for the dispersion to be abundance-dependent.
Possible values are |
prop.used |
optional scalar giving the proportion of all tags/genes to be used for the locally weighted estimation of the tagwise dispersion, allowing the dispersion estimates to vary with abundance (expression level). For each tag/gene the estimate of its dispersion is based on the closest |
method |
method for maximizing the posterior likelihood.
Possible values are |
grid.length |
for |
tol |
for |
verbose |
logical, if |
Maximizes the negative binomial weighted likelihood (a weighted version using the common likelihood given weight according the the smoothing parameter prior.n and the individual tag/gene likelihood) for each tag from the pseudocounts provided (i.e. assuming library sizes are equal), to give an estimate of the dispersion parameter for each tag (i.e. tagwise dispersion estimation).
"tricube"
local weighting is similar to that used by lowess
.
"movingave"
is much faster than "tricube"
and gives similar results.
"optimize"
is very slow if there is a large number of tags/genes to be analysed (i.e., more than 5000).
An object of class DGEList
with the same components as for estimateCommonDisp
plus the following:
prior.n |
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 |
tagwise.dispersion |
tag- or gene-wise estimates of the dispersion parameter |
Mark Robinson, Davis McCarthy and Gordon Smyth
Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing differences in tag abundance. Bioinformatics 23, 2881-2887
estimateCommonDisp
estimates a common value for the dispersion parameter for all tags/genes - should generally be run before estimateTagwiseDisp
.
y<-matrix(rnbinom(1000,mu=10,size=2),ncol=4) d<-DGEList(counts=y,group=c(1,1,2,2),lib.size=c(1000:1003)) d<-estimateCommonDisp(d) tgwdisp<-estimateTagwiseDisp(d, prior.n=10)