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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