I would like to compute the NUSE (Normalized Unscaled Standard Errors) from agilent microarray data.
Since the way I've found to do this is to use affyPLM library, using fitPLM function, which require an affyBatch object, I was wondering if there is any possibilities to use lmFit from LIMMA package to achive this goal ?
I could also create an affybatch object using my agilent data but still, I would rather have a function which take RGList (or MAList) object instead of affyBatch.
Is there a way to model probes and array effect using lmFit ?
NUSE is a quality measure that is specific to the particular probe-set structure of Affymetrix arrays. It depends on the fact that Affy arrays have a large (and constant) number of short probes for each gene. There is no corresponding quality measure for Agilent microarrays, which typically have one long probe for each gene.
You cannot create an AffyBatch object for Agilent data. Again, this concept is only meaningful for Affymetrix arrays.