Hi,
i was looking into the documentation for the rma() function in affy()
package, and was trying to figure out how exactly the background
normalization is done. I read all three papers cited in the rma()
documentation, but the most detailed explanation i could find was in Irizary
et al., 2003, where they state that they compute
B(PM_{ijn}) = E[s_{ijn} | PM_{ijn}]
where s_{ijn} is assumed to be exponential, and bg_{ijn} is normal.
I still don't understand what value is being computed here, neither am i
clear on what the correction looks like. i.e. if s_{ijn} is an
exponentially-distributed random variable, how is bg_{ijn} fit into this?
thanks!
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