Entering edit mode
Dear List,
I have a question regarding what weighting function to use when
analyzing Agilent data with limma. My question is whether or not it
makes sense to down-weight the control probes?
I have defined a weighting function:
wtfun.Agilent = function(x) {
okPopnOutlier = x[,"rIsFeatPopnOL"]==0 &
x[,"gIsFeatPopnOL"]==0
okNonUnifOutlier = x[,"rIsFeatNonUnifOL"]==0 &
x[,"gIsFeatNonUnifOL"]==0
okControlType = x[,"ControlType"]==0
as.numeric(okPopnOutlier & okNonUnifOutlier & okControlType)
}
And I would then use read.maimages() to read the data:
RG = read.maimages(targets, source="agilent", wt.fun=wtfun.Agilent)
This line assigns weight 0 (FALSE) to control probes and weight 1
(TRUE) to non-control probes:
okControlType = x[,"ControlType"]==0
As far as I can see, the normalization methods don't make explicit use
of the control probes and hence I would think it would be a good idea
to down-weight them. Any opinions on this?
Are there any way to make use of the controls?
Best,
Daniel