It is hard to help you because you don't actually show any evidence of
problems (small SDs are good, I would have thought, rather than bad),
because you're not using a standard limma analysis pipeline or
The recommend pipeline would be something like this:
RG <- read.maimages(files, source="genepix")
There is hardly ever any need to set flags or weights, and there is no
need for a for-loop.
At this stage it is valuable to set up a status variable to highlight
control probes. This is done using readSpotTypes() and
There are lots of examples of this in the User's Guide.
Then you can background correct and normalize with:
RGb <- backgroundCorrect(RG, method="normexp", offset=50)
MA <- normalizeWithinArrays(RGb)
To examine data quality, or to examine the success of the background
correction and normalization, the best way is to display MA-plots
and after each step. Eg.
to look at one array at a time, or
to produce a png file of MA-plots for all the arrays at once.