Hi, I did a normalizeWithinArrays(RG,method="printtiploess") and get this boxplot http://200.145.102.65:9102/normalized.data.png Is needed to do a normalizeBetweenArrays(MA.2,method="scale") ??? What you suggest me? I am not sure if a little difference between box is big or not. Thank you -- Marcelo Luiz de Laia Ph.D Candidate S?o Paulo State University (http://www.unesp.br/eng/) School of Agricultural and Veterinary Sciences Department of Technology Via de Acesso Prof. Paulo Donato Castellane s/n 14884-900 Jaboticabal - SP - Brazil Phone: +55-016-3209-2675 Cell: +55-016-97098526

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If you're going to be looking at the ratios only, normalising between arrays is rarely going to change anything (as the method aims to scale the range of intensities while leaving the ratios relatively unchanged). You can easily do a quick test and compare the results you get if you don't normalise between arrays, and using different methods (scale and Aquantile, for instance). When I try, I don't see much difference at all. I try to avoid altering the data (normalising procedures alter the data) unless I have a good reason to do so. On teh other hand, if you want to do some sort of single channel analysis, where you compare signal from one slide to signal from another, then you do need to make sure the slides are all in the same scale, and normalising between arrays makes sense. Also, as someone else said, you should not normalise between arrays experiments that by their own nature will behave very differently. I think that when we start doing arrays we tend to think "we-must-normalise... we-must-normalise" (imagine that with a Dalek voice ;-) and that anything that uses teh word "normalisation" is a good thing. However, it all depends on the biology of our experiment. Try to understand what your experiments are about and what is expected, and then think how it would make sense to normalise the data. Then see which of the methods available to you do what is necessary for your data. I find it useful to explore teh raw data (scatter plots, MA plots) and see what the trends are... and when I decide to normaise in a particular way, copmpare the effect of the normalisation to see if it did what I (roughly) wanted it to do. This allows you to build up a good feel for what the limitations are with any method, and you truly get to know your data. Jose Quoting Marcelo Laia <marcelolaia at="" gmail.com="">: > Hi, > > I did a > > normalizeWithinArrays(RG,method="printtiploess") > > and get this boxplot > > http://200.145.102.65:9102/normalized.data.png > > Is needed to do a > > normalizeBetweenArrays(MA.2,method="scale") > > ??? > > What you suggest me? > > I am not sure if a little difference between box is big or not. > > Thank you > > -- > Marcelo Luiz de Laia > Ph.D Candidate > S?o Paulo State University (http://www.unesp.br/eng/) > School of Agricultural and Veterinary Sciences > Department of Technology > Via de Acesso Prof. Paulo Donato Castellane s/n > 14884-900 Jaboticabal - SP - Brazil > Phone: +55-016-3209-2675 > Cell: +55-016-97098526 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor -- Dr. Jose I. de las Heras Email: J.delasHeras at ed.ac.uk The Wellcome Trust Centre for Cell Biology Phone: +44 (0)131 6513374 Institute for Cell & Molecular Biology Fax: +44 (0)131 6507360 Swann Building, Mayfield Road University of Edinburgh Edinburgh EH9 3JR UK