I have seen here in the BioC topics several threads concerning weighting of the Agilent data, howeever I didn't understand how important it is, how does it influence linear models and differential expression testing. In particular Agilent Feature extraction performs quite a lot of flagging and do normalization itself. What kind of flags is important to set for weight zero? Should control spots be weighted zero as well? Is it wise to use processed intensities (and do not use withinarray normalisation of Limma) instead of raw data? There are number of between normalisations, but which one to use? -- Dr. Nataliya Yeremenko Universiteit van Amsterdam Faculty of Science IBED/AMB (Aquatische Microbiologie) Nieuwe Achtergracht 127 NL-1018WS Amsterdam the Netherlands tel. + 31 20 5257089 fax + 31 20 5257064