My recent problems with extremely high dye bias turned out to be due to a defective dye batch. While it is expensive to do, if all the arrays were done with a particular batch and an anomalous result is found, it does pay to redo at least a couple of samples with a new set of reagents. --Naomi At 06:53 PM 7/20/2005, Gordon K Smyth wrote: >The fact that the dye effect is often highly significant is the reason >that it is recommended to >include it in the model. > >Gordon > > > Date: Wed, 20 Jul 2005 08:21:23 +1000 > > From: Mark Pinese <z3062573 at="" student.unsw.edu.au=""> > > Subject: [BioC] Significant dye bias using limma > > To: bioconductor at stat.math.ethz.ch > > > > Hello all, > > > > I have some questions regarding whether the significant dye bias I'm > finding in > > my analyses could be an artefact of my analysis method. > > > > I've been using limma to analyse a simple design comparing treatment > and control > > cases using dye swaps. As per suggestions in the recent limma Users' > Guide, > > I've added an intercept term to the design, and used it to find genes with > > significant dye effects. limma reports very many significantly > dye-biased genes > > (B-values as high as 12.7, 205 genes with B > 5), and very few > significantly > > differentially-expressed genes (highest B = 3.1). > > > > I'm using three biological replicates, each hybridised to two > dye-swapped arrays > > as technical replicates, on Compugen human 19k cDNA slides. > > > > Is such a strong result plausible, or due to me incorrectly analysing > the data? > > If so, what major pitfalls could I have blundered into? What sort of > > diagnostics can I try to test how reliable the model results are? > > > > > > Thanks for your time, > > > > Mark Pinese > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111