I have not reviewed the literature either, but I have analyzed experiments on 2-color cDNA, 2-color oligo Agilent, Affy and Nimblegen arrays, both model species and custom arrays for non-model species, with a variety of experimental designs. Based on this experience, I would have to agree with Sean. Platform, species, handling of the biological material, experience of the lab personnel, micro-environment, ... make a huge difference. But the S/N is certainly orders of magnitude smaller than 30000:1 - maybe more like 2:1 on a single array. Of course, partly that is because of the definition of signal - do you mean the level of mRNA in the sample (which I think you mean in spectroscopy), or the mean level under the conditions of interest (which is what we mean in most microarray studies)? --Naomi At 07:04 AM 11/10/2005, Sean Davis wrote: >On 11/10/05 6:18 AM, "narinder.singh at diagenic.com" ><narinder.singh at="" diagenic.com=""> wrote: > > > Can somebody point to litterature related to S/N ratio in > microarray data. In > > spectroscopy the S/N ratio is typically 30000:1. From what I have > gathered S/N > > ratio is a big problem in microarray data. Is there any > litterature/study with > > corresponding S/N numbers for microarray data for commercially available > > platforms. > > > > Thanks in advance. > >Narinder, > >I don't think this is a well-understood property of array technology. S/N >is at least probe-dependent and like sample-dependent as well (RNA quality, >etc.), not to mention operator dependent, ozone-level dependent, humidity >dependent, protocol dependent, and many others. Some experimental designs >(particularly with two-color arrays) can GREATLY affect the S/N ratio at the >level of the final analysis (which is what counts). I'm not giving an >answer directly, because I'm not sure that one exists and if it does, I >think it applies only to a specific set of samples in a specific lab on a >couple of platforms, etc. > >Perhaps someone else has reviewed the literature on this subject and can >give you a better answer. > >Why do you ask? > >Sean > >_______________________________________________ >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 Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111