vooma(y, design=NULL, correlation, block=NULL, plot=FALSE, span=NULL)
voomaByGroup(y, group, design=NULL, correlation, block=NULL, plot=FALSE, span=NULL, col=NULL, lwd=1, alpha=0.5, pch=16, cex=0.3, legend="topright")
matrix
, EList
object, or any similar object containing expression data that can be coerced to a matrix.logical
value indicating whether a plot of mean-variance trend should be displayed.y
.nrow(y)
.0
for fully transparant to 1
for fully opaque.counts
was a DGEList
objectvooma
is an acronym for mean-variance modelling at the observational level for arrays.vooma
estimates the mean-variance relationship in the data, and uses this to compute appropriate weights for each observation.
This done by estimating a mean-variance trend, then interpolating this trend to obtain a precision weight (inverse variance) for each observation.
The weights can then used by other functions such as lmFit
to adjust for heteroscedasticity.
voomaByGroup
estimates precision weights separately for each group. In other words, it allows for different mean-variance curves in different groups.
voom
, arrayWeights