Hi, i want to work on normalized intensity values in my experiment (oligo arrays). To do this, I first need to normalize data with a "within array normalization", followed by a "between array normization". So, I used printtiploess function followed by the Aquantile function. Just for testing purpose, I also tried with with "quantile" method and I was surprised to see that toptables were really different: resulting p-values were better with this second method. And, if I take the first 100 genes in the toptables, 50% are different. As quantile function normalizes again ratios, does it mean that printiploess method did not correctly normalized my ratios ? Here are my first genes: PrinTipLoess + Quantile: "logFC" "AveExpr" "P.Value" "8802" 2,44 10,86 4,20E-17 "9786" 1,96 10,77 7,51E-17 "8906" 2,24 10,75 7,21E-16 "11808" 2,14 10,74 8,86E-16 "5276" 1,93 10,71 1,55E-15 PrinTipLoess + AQuantile: "logFC" "AveExpr" "P.Value" "8802" 2,73 10,84 1,69E-15 "7678" 1,51 7,96 4,45E-15 "7657" 1,48 8,59 6,59E-15 "9254" 1,71 8,66 8,18E-15 "9786" 2,41 10,75 2,04E-14 Sincerely, Lucie