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Dear all I apologize for cross-posting, but first it is accepted custom to thank the repliers and give a summary, and second I have still the feeling that this problem might be a general statistical problem and not necessarily related to microarrays only, but I might be wrong. First, I want to thank Robert Gentleman, Mark Kimpel and Mark Reiners for their kind replies. Robert Gentleman kindly

Dear Ioannis Thank you very much for pointing me to meta-analysis. Although it may not solve my problem with the normalization, it gives me some other options to display the different correlation coefficients. One possibility is the use of Funnel plots, which are even available in library(rmeta). Another possibility is the use of forest-plots, as implemented in rmeta as metaplot. Sorrowly,

...j) would choose ``distant'' parts of the periodic cycle. Unfortunately, we don't know what exactly happens in the S-plus code for set.seed(i), namely, .C("setseed", as.integer(i)) However, I have found out the following which should suffice : 1) Only .Random.seed[4:6] are varyied by set.seed, i.e., after set.seed(i), .Random.seed always is 1 2 3 4 5 6 7 8 9 10 11 12 [1] 21 14 49 * * * 32 22 36 23 28 3 X4 X5 X6 Which means that only the 'congrval' {Venables & Ripley, 2nd ed., p.166-167} is varied 2) X4 is always == 16*(...

...---- X ###--- Mon, Sept. 15, 1997 ---------- X ##- Unfortunately, we don't know what exactly happens in ##- the S-plus code for set.seed(i), namely, .C("setseed", as.integer(i)) ##- However, I have found out the following which should suffice : ##- ##- 1) Only .Random.seed[4:6] are varyied by set.seed, i.e., ##- after set.seed(i), .Random.seed always is ##- ##- 1 2 3 4 5 6 7 8 9 10 11 12 ##- [1] 21 14 49 * * * 32 22 36 23 28 3 ##- X4 X5 X6 ##- ##- which means that only the 'congrval' {Venables & Ripley, 2nd ed., p.166-167...