Hello all,

I'm using vsn to transform a single-colour microarray experiment with 4 lab
lines collected a 5 times, and three biological replicates (60 slides).
Each EST is printed in duplicate, sometimes adjacent to one another and at
other times at the ends of rows and beginning of the following row.

Is it valid to vsn-transform the dataset prior to averaging the duplicate
spots?  The few papers I have that explicitly address minute details of data
preparation do not present consensus - some people average before
normalization, and others use normalization to decrease the variance among
duplicate spots.

It seems to me that providing as much information as possible would be of
benefit to stabilizing variance in a dataset, but on the other hand it seems
that pseudoreplication might bias vsn's accounting for differetially
expressed features.  I'm not much of a statistician, and we're an isolated
facility so I hope that someone can shed light on what is becoming a lively
debate.

With thanks,

Maurice

	[[alternative HTML version deleted]]

